Long Stay Patient Dashboard in Metro South

Aim

The aim of the MSH Long Stay Patient Dashboard Project was to develop and implement a standardised workflow and dashboard linked to ieMR to provide a real-time view of long stay patient status at a facility and HHS level, detail individual Long Stay discharge barriers and long stay trends.

Outcomes

• The MSH Long Stay Dashboard, demonstrated an ieMR workflow can be utilised to identify long stay patients.
• The MSH Long Stay Dashboard has created a single source of truth for tracking MSH Long Stay Patients at a health service, facility, and individual patient level.
• The MSH Long Stay Dashboard has improved data accuracy and quality.
• The dashboard has streamlined long stay patient data reporting processes and significantly reduced the time taken to complete the quarterly long stay patient census.
• MSH conducted baseline measures prior to the MSH Long Stay Dashboard implementation assessing
  staff perceptions of data accuracy, impacts and satisfaction of reporting long stay patients across MSH. Follow up measures of 6-8 months post implementation are currently being collected.

Background

Patients who remain in hospital after being medically cleared for discharge is a long-standing issue across Australian health services. Despite local Metro South Health (MSH) and statewide initiatives, the prevalence and impact of long stay patients residing in acute beds across MSH facilities remains substantial.

Key impacts of long stay patients on MSH include:

1. reduced organisational efficiency and capacity to meet the needs of the community’s health care, through direct impacts to Emergency Department and QAS workflows
2. major impacts for delayed patients and families including psychological distress, financial imposition, functional decline, and iatrogenic events
3. increased workload burden due to complex work tasks and advocacy processes resulting in alterations to clinical care protocols, overall reduced direct patient clinical care time, and impacts on staff job satisfaction and morale
4. the prevalence of people with highly complex psychosocial care needs residing inappropriately within an acute health care setting has potential for increasing risks to themselves, staff, and co-patients.

In April 2024,  it was identified that MSH required reliable and focused datasets to increase real-time and trend data visibility of long stay patients. Accessing usable long stay data in MSH was impacted by the use of both PFM/Kyraflow and ieMR as the primary sources of  tracking long stay and discharge delays across MSH. The use of multiple platforms reduced the clinical utility of the information available, and the accurate identification and mapping of long stay patient census data was a manual and time-consuming process.

MSH Staff reported it took an average of 21.35 minutes per patient to identify and record long stay patients details prior to the dashboard implementation. Baseline staff surveys indicated that the identification and reporting of MSH Long Stay Patients added  slightly to staff workflows and had staff had mostly “neutral” to “somewhat negative” perceptions regarding data accuracy, complexity and satisfaction of pre-existing processes. The development of a dataset with the capacity to provide a real-time ‘dashboard’  view of long stay status, detail on individual long stay patient barriers, and long stay trend reporting was considered highly desirable. Access to real-time visibility of delays to discharge helps to support decision making around the diversion of resources where required and streamline monitoring and reporting processes. The ability to store data has also provided the ability to track initiatives against outcomes and inform future service planning.

Discussion

The implementation of the MSH Long Stay Patient Dashboard has delivered many positive outcomes to MSH as an organisation, which have extended to patients under its care:

1. a clear and agreed definition of MSH Long Stay Patients
2. a single source of truth for tracking MSH Long Stay Patients, which also utilises the patient record in ieMR
3. improved data accuracy, efficiency and comprehensiveness of long stay patient reporting initiatives for both local MSH and statewide initiatives, such as the long stay census
4. follow up measures of staff satisfaction and perceptions of data accuracy and reporting complexity/ demands 6-8 months following implementation are currently being captured.

There were multiple factors which led to the successful implementation of the MSH Long Stay Patient workflow and dashboard, these included:

• support and governance from both Executive and the MSH Long Stay Committee
• clinical champions of this initiative
• utilising a simple workflow on a single platform (ieMR) to identify and report MSH Long Stay Patients, supported by endorsed data definitions and business rules
• MSH Data & Analytics linking data from multiple systems into an easily digestible dashboard format, providing high level reporting metrics and clinical utilisation via the ability to drill through to a patient level
• the ability of the MSH Long Stay dashboard to clearly identity data entry errors. Despite the success of the MSH Long Stay dashboard some limitations of this workflow exist:
• the ieMR alerts and problems functionality only allows for two data entry fields, which are free text fields, increasing the
  potential risk of data entry errors. To mitigate this, the MSH Long Stay Patient dashboard was coupled with other data sources and was built to clearly identity data entry errors.
• the ieMR alert and problem functionality is at the patient level, meaning this alert will continue to be active on the patient’s ieMR record until manually resolved. This functionality has clinical utility for other workflows and requires clinicians to manually review the patient’s alerts and problems on each admission and perform the necessary reconciliation. To ensure data accuracy and prevent recording of previous long stay patients who are having acute re-presentations, the dashboard has inbuilt logic that excludes patients whose most recent long stay alert was entered prior to their admission date
• MSH has separate HBCIS instances for each facility. Due to dashboard logic, a new “Long Stay Hospital Inpatient” alert is required to be entered if a Long Stay Patient is transferred to another MSH facility. The MSH Long Stay Patient dashboard and associated workflow has received positive interest from other HHS’s.

Future directions for this initiative include improving the capability of the ieMR to capture Long Stay Patient information in a user-friendly format. Through partnering with other HHS’s, there may be potential opportunities to optimise the ieMR to improve the clinical documentation and collection of defined data points of long stay patients, sub-acute patients and patients with disabilities such as barriers to discharge, QCAT information, NDIS information and disability identifiers.

References

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