Data can play a critical role in planning and delivering better care as well as measuring patient outcomes, says Robert McGough and Gemma Badger of Hill Dickinson LLP
Health systems worldwide are stretched and grappling with the question of how to deliver more effective high-quality care across populations at an affordable cost. Data is key to this conundrum; however, is it being used as effectively as it could be? Undoubtedly, the answer in many cases is no. What do we need to do differently to promote change?
Our premise is that a more integrated data driven and value-based approach to healthcare planning and provision could be used to incentivise actions that improve patient outcomes at the most efficient cost, while also responding to the other challenges in terms of parity of service access and quality. The foundations to enable value are laid through data–effective transparent collection, analysis, and application of this resource. Once those foundations are in place, supporting structures, including value-based financial and contracting approaches can then come more readily into play to incentivise and monitor the progress of improvements.
A key aspect of this approach would be the development of a culture within healthcare systems of prioritising learning from data over penalties.
Data issues
Common issues hampering the effective
use of data within healthcare include:
• Inaccessible documents – paper based or scanned systems
• Siloed data – within different bodies, departments or systems
Despite holding the data, these basic systemic issues make it difficult to analyse, utilise and share it. Legal, contractual and regulatory frameworks can also restrict the management of data, making it difficult for systems to use it to its full potential. However, these issues, once identified, are not insurmountable, especially once all the stakeholders involved commit to working together to tackle them – indeed, some have already created shared care records to do so.
Data-driven solutions
Moving to a new value and data driven way of working requires us to rethink the systems where healthcare delivery is organised, contracted for, procured, measured, and reimbursed. Achieving this goal requires a clearer link to be made between the form of legal contracts and finance / remuneration incentive models (and the procurement exercises undertaken for them), together with changes to the way that data sets are used and correlated.
Insight generation will also direct action, but this is only possible when sufficient resource and capability is given to analyse datasets. As a result, risk adjusted outcomes can identify patterns and trends that lead to actions that add value, impact organisational strategy, and improve patient outcomes.
Wider datasets which could be utilised for this approach include:
• Clinical data
• Financial data
• Procurement data including medical device usage
• Litigation data
By coordinating data from these sources, healthcare systems can start to create a transparent learning environment that is focused on incentivising the right behaviours to encourage better clinical and operational outcomes. This learning environment will allow systems to objectively identify areas where care can be improved, track the performance of providers, and make changes to the system that will lead to better outcomes for patients.
Supporting structures
Actionable insights analyses are a powerful tool to drive improvements in clinical performance and patient outcomes with results then linked into a contractual and finance model which incentivises improvements and focuses on data sharing and good practice. The focus in this approach is on incentivising shared learning and best practice rather than levying financial and contractual penalties on organisations which may already be struggling, forcing them to make more difficult decisions about resource usage, which then further impact patient outcomes.
Current forms of contract in many healthcare systems are input-based (payment for device, payment by results or a block service payment) and focused on financial aspects with penalties and potentially a route to swift termination for poor operational performance. Where aspects of outcomes are used (such as PROMs) these often do not form a significant part of the finance, with numerous other KPI measures used that are based on inputs or processes rather than clinical outcomes.
The requirement for input-based working and the use of the contract as a tool to input additional guidance and policy shifts has led to a very complex contracting structure. Unfortunately, this resulting structure has perpetuated the current way of working, which does not incentivise better than baseline care, innovation or collaboration.
However, integrated data-driven approaches could change this structure. One method could utilise a form of value-based contract and incentive model linked to the forms of data listed above, together with incentivised sharing of data and best practice to improve clinical performance within a learning environment.
For example, if risk adjusted clinical outcomes data shows that a certain group of patients is more likely to experience poor outcomes for a procedure in one hospital/system or area, rather than a penalty, this information can be used to identify and reward interventions and improve clinical practice and outcomes for this group. More broadly, this information can be used to make changes to the system in terms of pathways and resourcing that can improve care for patients and incentivise sharing best practice through financial and operational shifts.
Overall, there is an opportunity for healthcare systems to reimagine how they use and co-ordinate wider data transparently across several different areas.
By carefully drafting contracts to deploy data transparently and incentivise the outcomes that the patients and the system want, those contracts can identify and reward the sharing and development of best practice. These results in turn serves to create a supportive learning environment in which better patient outcomes can be achieved.
This article is a summary of themes explored in a paper prepared by C2-ai and Hill Dickinson on “Integrating data sources to create a new innovative learning environment for healthcare systems”. Please contact Rob for more details.