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Why Conventional Change has to Change: A Better Way to Improve… Part 2

Albert EinsteinYesterday I outlined the problems inherent within conventional approaches and thinking about change management. All too often conventional approaches result in no or little positive change for either service users or taxpayers. Albert Einstein was right: to solve problems and improve our thinking has to change. Indeed, real improvement comes through learning by doing and reflecting on these results. It must also be rooted in research that provides data-driven evidence.

Essential to the acquisition of hard-data is knowledge of customer demand that illustrates patterns of need set against the deployment of resources. Good service (as experienced by the customer/patient/service user) always pays, it never costs. The inability to deliver service is paradoxically expensive and the real ‘gold-plating’: it means in the public sector patients or service users receive either too little and then either ‘represent’ to the service or (in the private sector) customers leave altogether.

Conversely, reviewing services from the customer/patient/service user perspective reveals the folly of conventional change management with its preoccupations on activity assumptions, arbitrary plans and make-believe monetary savings which rarely materialise. Improvement begins with adopting a customer mind-set, studying services and putting pre-configured assumptions of what works aside. Use innovative methods to understand how and why services perform the way they do and what it takes to get them better for those that need to use them.

A Better Way to Conceive Improvement

Intelligent change starts with turning convention on its side, researching performance of local NHS and care systems through the external lens of the patient. The way to realise better service and less cost begins with taking a different, horizontal view. Patients flow through healthcare systems.

Adopting a ‘Front-to-Back Thinking’™ mind-set is about recognising that activity and costs are a consequence of what you do not why you do something. Performance improvement comes from studying patient-level demand; analysing the nature of activity that this demand generates and achieving sustainable cost savings through the elimination of activity waste. How well an organisational system meets patient needs should inform both strategy and costs.

Studying patient demand allows for intelligent system and service redesign solutions around cohorts of patients, not pathways. The principal work is two-fold: research and redesign. The former is evidence-informed problem identification through data analysis.

Research is undertaken to understand patient-demand by looking at the ‘what, where, who, why and when’ of their healthcare usage. It is important to recognise here that the requirement is to utilise both quantitative and qualitative research techniques. A common error with many analytical models is to draw linkages between correlation and causation or indeed assert causality as a consequence of data analysis. Data analysis asks ‘what’ questions which need to be linked to demand analysis’s pursuit of ‘why’ to authenticate findings.

This phase entails analysis of time-series consumption and case-mix data; encounter data to understand customer activity and patterns of usage as well as the type, frequency, volumes and predictability of customer demand together with an understanding as the balance in value versus non-value activity. The work provides patient segmentation into meaningful typology groups which forms the foundation for subsequent improvement work.

Redesign implies a set of sequential steps to undertake intelligent improvement activity. Such Improvement must focus on redesigning the care models and systems around patient cohorts, beginning with the ‘vital few’ patients who, although small in number, consume disproportionately large amounts and activity and costs.

It involves using knowledge gleaned in the research phase to undertake prototype service redesign activity. Clarity of the patient purpose is paramount; as is patient-centred performance metrics; redesigned systems, processes and roles; experimentation with operating models and continuous feedback loops to ‘learn to improve and improve to learn’.

Teams of interdisciplinary professionals are assembled and given autonomy to work together first understand and then meet the holistic (medical and non-medical) needs of these patients, who themselves set the boundary. Flexible services and systems are harmonised according to patient need. The role of leaders also changes, from mandatory monitoring in board-level meetings to problem-solving issues that beyond the control and scope of local interdisciplinary teams.

Key skills that are required include medical and technical but extend more importantly to interpersonal, organisational and problem-solving abilities. The focus is on decreasing end-to-end service times, ensuring more work is done right-first-time; reducing or removing activity that adds no value to the patient thereby preventing such patients from boomeranging around the system.

Here the work involves alterations to budgets, roles, measures and, where necessary, technology. Importantly, the purpose is to develop the redesign and determine its anticipated economies through internal base-lining of current performance via patient-level not service-line reporting.

Following the prototype period, leaders make an informed choice about the benefits from adopting the new (systems) design including further roll-out opportunities. This approach is encapsulated in the Consumption Demand Method™ which enables the emergence of better services that act as testing grounds for continuous improvement set against a better understanding of patient demand.