A Computer System, Method and Program to Assess The Quality of Healthcare

Outcomes

The present invention relates to assessment of the quality of healthcare provision, based on actual healthcare outcomes. This method can be applied for the audit and the evaluation of healthcare provision quality in hospitals, community care centres, residential care and elsewhere.

Owing to the increasing healthcare costs across the world, most Governments (including Japan, Singapore, UK and USA) and leading technology companies (such as IBM, Google and Microsoft) are focussing and investing in the area of improvement of healthcare quality provision, and are interested in systems that conduct quality assessments or audits. The escalating demand for improving the quality of healthcare provision has influenced both the public and private health sectors; examples include: The UK National Health Service (NHS) Outcomes Framework (NHS OF) and NICE quality standards in the UK; Saint Luke's International Hospital's Quality Indicator (Ql) in Japan; and Cleveland Clinic's Health Hospital Performance Measures in USA.

Preventable Adverse Patient Safety Events and other re-admissions as a result of low quality healthcare provision can cost up to 67% in excess; more than 70% of adverse events may result in disability lasting up to six months, and more than 15% of serious adverse events may lead to permanent disability or death. Almost 1 out of 5 patients discharged from the hospital experience an adverse event within 3 weeks, and 2/3rd of them are due to Adverse Drug Reactions (ADRs). In the US, readmissions within 30 days account for $15 billion p. a. of Medicare Hospital's spending. From 1999 to 2008, the annual number of ADRs has increased by 76.8%, which is applying an extra cost on the NHS. In the UK, NHS spends £460 million p.a. to treat 250,000 patients admitted to hospitals due to preventable ADRs to prescribed medicine; and several ADRs have been reported in the UK. Hospital admissions due to ADRs constitute more than 5% of the total admissions and cost approximately £0.5 billion per annum.

According to the revised Operating Framework for the NHS in England 2010/11 (re- enablement and post-discharge support) the intention is to ensure that hospitals are responsible for patients for 30 days after discharge - i.e. hospitals are not paid for re- admissions within 30 days of discharge as a result of poor quality of care or inappropriate treatment for a condition. Consequently, the healthcare providers are held accountable for the 'quality' of healthcare outcomes.

Since a huge interest and investment has been witnessed in systems that conduct quality assessments and/or audits, development of such tools and technologies that provide (as a service) auditing, evaluation, and/or management of healthcare provision quality, based on healthcare outcomes, has become absolutely imperative. Generally speaking, there are two different ways in which the "quality of healthcare provision" can be assessed:

First, the Process-centric approach - where the "quality of healthcare provision" is defined in terms of the adherence of a process to a particular clinical pathway or workflow (i.e. steps in a healthcare procedure such as taking blood tests, conducting MRI scans, giving specific medications, etc.).

Second, the Outcome-centric approach - where the "quality of healthcare provision" is defined in terms of the actual medical outcome of a clinical procedure (i.e. result of a process such as blood pressure reading, blood glucose level, or heart rate, etc.).

So "what happens" to a patient (that is, the subsequent state of the patient) after undergoing a clinical procedure (or process) or after a particular illness/wellness milestone is referred as the "outcome" of that process; and this outcome can be used to measure the quality of that process.

Previously, quality assessment has been performed primarily by using the process- centric approach, and until now there has been a lack of research conducted in terms of implementing the outcome-centric approach for assessing the quality of healthcare provisioning. Currently, process managers assess the actual clinical workflows (or processes) in order to improve the healthcare processes. For example, they may identify loopholes and inconsistencies that are a cause of low quality. However, the patient's healthcare (clinical) outcomes are not assessed for this purpose, and these may be seen as the true indicators of quality of healthcare provisioning. For either view of healthcare assessment, there is a major problem inherent in the vast amount of data which requires processing in order to provide an accurate assessment.

According to invention embodiments there is provided a computer system operable to assess the quality of healthcare outcomes comprising an outcome measurement component; and an outcome assessment component; wherein the outcome measurement component is configured to convert received non-numerical healthcare outcome data into a numerical format; and the outcome assessment component is configured to receive a request for healthcare outcome data to identify at least one suitable assessment parameter to compare the converted healthcare outcome data from the outcome measurement component for the at least one parameter with comparison data and to provide a quality score.

The outcome measurement component and outcome assessment component (sometimes referred to herein as measurement and assessment component for brevity) act together to significantly reduce data transfer and intermediate data storage within a computer system for assessment of healthcare outcomes. Conversion of non- numerical healthcare data into a numerical format significantly reduces overhead for data transmission and storage, and this in combination with use of the outcome assessment component to identify assessment parameters for specific occasions cuts down data transfer within the system and allows efficient processing of healthcare audit and evaluation.

The term "condition" is intended to refer to a health state, such as an illness, disease, remission or other state of wellness etc. The term "milestone" is used herein to refer to a particular stage in the condition or health state. Exemplary milestones are discussed hereinafter.

The term "computer system" can refer to any computing system with memory, processing capability and inputs and outputs, for instance to a simple system with computing functionality in a single location (for example a server and possibly links to various devices) or to a more complex partially or fully distributed system or to a computer system provided as a "cloud" service. The skilled reader will appreciate that the request for health outcome data may specify the population to which the request is applicable, which may be an individual, a department, a hospital, or a region as examples. Thus the quality assessment may not be limited to a specific condition (i.e. illness or disease) but can be applied to a qualitative assessment (which is not disease-specific) by population specific request for performance of a particular hospital (e.g. an institution) or performance of a healthcare institution in a geographical region. In this case, the suitable parameters may be defined implicitly or explicitly as all the parameters available for that population. The comparison data can be any suitable data, for example, expected data for normal results which may be provided by a much larger population, expert database or direct input. The quality score can be any type of quality measurement, such as a numerical score, text score or visual indicator. In some embodiments, the request is related to at least one specific condition and at least one milestone in that condition and the assessment parameter is suitable for the specific condition and milestone.

Preferably, the computer system of invention embodiments further comprises a process manager linked to the outcome measurement component and outcome assessment component, preferably via a network; wherein the process manager is configured to send the request; and the outcome assessment component is configured to transmit the quality score to the process manager. Thus a process manager can be a part of the computer system and linked into the measurement and assessment components over a network as necessary. The process manager may essentially correspond to the user end point and can control the process of quality assessment. Turning to the measurement component, this may be configured to receive healthcare outcome data over a network in the form of numerical data and non-numerical data and to convert the non-numerical data to numerical data using a mapping rule database. The conversion gives a quality score corresponding to the non-numerical data. The outcome measurement component may also be configured to assign a score to the numerical data.

That is, a mix of data can be used in the quality assessment as long as it is all converted to numerical data. The mapping rule database helps with this conversion and preferably contains numerical and non-numerical information as to health states with respect to milestones (of the wellness/illness cycle) for a condition, and a (numerical) scoring system for the numerical and non-numerical information. The outcome measurement component may be configured to produce a healthcare outcome translation metric for the healthcare outcome data. This outcome translation metric applies the mapping database rules to the outcome in question.

The outcome measurement component may be configured to receive healthcare outcome data from more than one source over one or more networks. In many embodiments, the measurement component can receive healthcare outcome data from numerous different sources, for example, over several networks.

In order to provide comparison data, it is appropriate to produce data in a similar fashion to the way the outcome data is processed. Therefore preferably an expected healthcare outcome component is configured to receive expected outcomes for a specific condition and milestone in that condition in the form of numerical data and non- numerical data and to convert the non-numerical data to numerical data using the mapping rule database, thus providing the comparison data. The expected outcomes (perhaps for all the conditions and milestones which are to be considered) can be added by one or more medical experts.

The expected healthcare outcome component may be configured to produce a healthcare outcome translation metric for normal profiles with respect to age, gender and/or disease/condition and/or other factors such as ethnicity and/or genes.

The outcome assessment component is an important part for efficient operation of invention embodiments. Preferably, the outcome assessment component is operable to receive the converted healthcare outcome data and expected healthcare outcome data, and to compare them using a formula database, and to provide an overall quality score.

The outcome assessment component may also calculate harm, using a harm metric database in conjunction with the converted healthcare outcome data. This can be taken into account in the overall quality score.

Preferably, the formula database contains formulas for quality assessment of healthcare according to conditions and milestones within the conditions.

Preferably, the harm metric database is a medical database containing possible negative indicators and a score for these indicators according to a condition and the milestone within the condition. Clinically labelled examples of negative indicators include side effects, or Adverse Drug Reactions (ADRs), etc. The negative values can be derived from negative side-effects but also can derive, for example due to infections or dirty conditions picked up from the previous visit (at the care facility) or clinical negligence.

As mentioned above, the computer system of invention embodiments possibly has distributed functionality. For example, the process manager can be spatially separate from the measurement and assessment components. The function of the process manager may be to select a population for evaluation and/or to evaluate the quality score as well as to send the original request for healthcare outcome data. The system components are capable of working in distributed environments, therefore, they could be on different servers. In some embodiments, the measurement and assessment component are provided together on a server (or other computer) referred to herein as a functional server because it provides the functions of measurement and assessment. The skilled person will appreciate that these two components are defined separately but may be provided as a single module of hardware/software/firmware. Preferably the mapping rule database is provided on the same functional server as the measurement and assessment component. Equally, the database for the converted healthcare outcome data (the converted results to be assessed) and/or the formula database may be held on the functional server. In contrast, the other databases 12 050382

7 referred to herein including the data sources fed into the measurement component and the database for the normal expected healthcare outcomes and harm metric database may be held on a separate computer referred to herein as a database server computer which may communicate with the server computer over a network such as a wide area network.

According to embodiments of a further aspect of the present invention there is provided a computer-implemented method operable to assess the quality of healthcare outcomes comprising converting received non-numerical healthcare outcome data into a numerical format, receiving a request for healthcare outcome data, identifying at least one suitable assessment parameter comparing the converted healthcare outcome data for the at least one parameter with comparison data and providing a quality score.

This method is equivalent to the system aspect and therefore features of the system as herein before described are applicable equally to the method aspect. The steps of the method may be carried out in another order and still achieve desirable results. Equally, the various components described and/or process manager may be provided by the same hardware resource, and/or the various databases described may use the same memory resource. The databases can be provided as linked tables, as described in more detail hereinafter.

According to a further aspect there is provided a computer program which when executed on a computer carries out the method of the preceding method aspect and/or which when downloaded onto a computer system it to become the computer system of the apparatus aspect as variously set out above.

Preferred features of the present invention will now be described, purely by way of example with reference to the accompanying drawings, in which: Figure 1 is a diagrammatic representation of the functionality in a computer system according to an embodiment of the present invention;

Figure 2 is a diagram showing a computer system according to an embodiment of the invention; Figure 3 is a flowchart showing conversion of non-numerical data to numerical data according to an invention embodiment;

Figure 4 is a flowchart of creation of expected healthcare outcomes for use in an embodiment of the invention;

Figure 5 is an overview of the healthcare outcome assessment according to an embodiment of the present invention;

Figure 6 is a more detailed flowchart showing steps in outcome assessment in an embodiment of the present invention;

Figure 7 is a diagram demonstrating one of the technical advantages of the invention embodiments;

Figure 8 is a schematic diagram of hardware which can be used in invention embodiments;

Figure 9 is a diagrammatic overview of a healthcare system in which embodiments of the present invention can be used;

Figure 10 is a schematic view of areas of use of the present invention within a healthcare system;

Figure 1 shows comparative data in graph form obtainable by an embodiment of the present invention and used to isolate a quality concern; and

Figure 12 is an episode tree demonstrating defined goals and how they are assessed in a particular episode of a condition;

Invention embodiments assess the quality of healthcare provision, which is based on actual healthcare outcomes for calculating the quality score (sometimes referred to as Q-score herein). This allows auditing and evaluation of the quality of healthcare provisioning in institutions such as hospitals, community care centres, and residential care, and in the community. The method and system can provide reduction in re- admissions due to low quality of care.

Invention embodiments assess the quality of healthcare provisioning using the outcome-centric approach to calculate the quality score (Q-score) for healthcare provided to patients.

Figure 1 is a general embodiment showing how invention embodiments are implemented in an efficient way which minimises data transfer and storage. A request for a quality score relating to one ore more particular condition(s) and milestone(s) within the condition(s) is sent to an outcome assessment module. This module collects data for the condition(s) and milestone(s). Firstly, it must identify one or more parameters which can be used for assessment in those circumstances and then it can use comparison data for an expected outcome with respect to the parameter(s) and for the healthcare outcome data which is being assessed. The outcome data which is being assessed may require conversion by an outcome measurement module. In particular for non-numerical healthcare outcome data, but also for numerical data the outcome measurement module can map the data to a numerical scale for ease of data compression and also for ease of comparison.

Comparison of the parameter value or values for the healthcare outcome data to be assessed and for the expected outcome data will provide a quality measure or score. The following description is of a more detailed embodiment and relates to a method and system to assess the quality of healthcare provisioning by calculating the Q-score based on actual healthcare outcomes. The actual healthcare outcomes resulting from a clinical procedure or care provisioning include signs (which are numerical, sometimes referred to as objective or measurable data such as blood pressure, mobility, glucose levels, etc.) and symptoms (which are non-numerical, sometimes referred to as subjective or non-measurable data such as pain, confidence level, speech, or facial expressions). The system of this more detailed embodiment is depicted in Figure 2, which shows the interaction of various systems components.

Database 204 contains direct data from hospital information or management systems such as Electronic Medical Records (EMRs), Electronic Health

Records (EHRs) containing actual results of healthcare provisioning

Database 208 contains direct data from Personal Health Records (PHRs) systems containing actual results of healthcare provisioning

Database 205 is the manual input from healthcare provider (nurse, doctor) or the patient entering the actual results of healthcare provisioning

Here, data is collected from three different sources in order to provide healthcare outcome measurement. These three data sources feed data to the healthcare outcomes measurement component 200 in the form of both numerical and non- numerical data. Healthcare outcomes measurement component 200 may function intermittently/continuously to build up database 207 of actual healthcare outcomes. Alternatively or additionally, the database 207 may be updated when there is a request from the process manager, for example as to a certain condition and milestone.

The healthcare outcomes measurement component 200 uses a mapping rule database 206 to create a healthcare outcomes translation metric to provide results of the healthcare provisioning which is being assessed. The mapping rule database 206 is a medically driven database with a score sheet for health states including scores for assessment parameters for each milestone or goal. The healthcare outcomes translation metric applies the rules to the data from sources 204, 208 and 205, and may take age, gender and other information into account. The database of actual healthcare outcomes 207 feeds into the healthcare outcomes assessment module 102. 102 also receives input from database 303 which contains "normal" expected healthcare outcomes for comparison, a formula database 405 and a harm metric database 406. The normal expected healthcare outcomes have already been converted to numerical format if necessary, as explained in more detail hereinafter. The formula database contains formulas for each condition and milestone (or goal) and a way of relating the variation between actual outcomes and expected outcomes to provide a quality score. The harm metric database is optional. It relates to possible negative effects at any particular milestone and may be provided from an existing medical database. The negative values from the harm metric database may be taken into account in the healthcare outcomes assessment module 102 in conjunction with the variation between actual and expected outcomes to provide the quality support. The metric for harm also preferably relates to specific conditions and milestones and may give a harm score. In most invention embodiments, the formula database does not take any potential harm values into account, and these are considered solely in healthcare outcome assessment module 102.

Processing of an individual enquiry as to quality of healthcare provisioning is triggered by the process manager 100. The process manager may be a hand held terminal 100 or other terminal with a graphical user interface. The user sends an enquiry specifying a particular condition, shown as query 209 with Disease and Goal. This triggers action of a healthcare outcomes assessment to compare a population (for example an individual, a hospital, a department, a geographical region, etc) against expected healthcare outcomes. The population may be predetermined or also determined within the request.

The assessment component provides a quality assessment as Q-Score 309. Figure 3 is a flowchart for the outcome measurement component 200, which provides converted actual healthcare outcomes and creates the translation metric for the actual results (for assessment) of the healthcare provision

The healthcare outcomes measurement component 200 reads objective (signs) and subjective (symptoms) data from data sources 204, 208, and 205 in step 201. The healthcare outcomes measurement component 200 then creates healthcare outcomes translation metric in step 202 for the actual results of the healthcare provisioning for a particular disease by using the mapping rule database 206. Mapping rule database 206 contains mapping of subjective (non-numerical) healthcare outcomes to a measurable scale, e.g. "smile" to numerical grade 3 or "speak" to numerical grade 7.

The healthcare outcomes measurement component 200 then outputs results to actual healthcare outcomes database 207 in step 203.

Figure 4 shows how the expected outcomes are provided by obtaining normal expected healthcare outcomes and create translation metric for the normal profiles. They may be produced per request from the process manager (that is, by condition and milestone) or there may be a pre-populated database of expected outcomes for all the required conditions and milestones, which is replenished with new results as appropriate.

In step 301 , both objective (signs) and subjective (symptoms) data for comparison is obtained by manual input (or evidence-based data) 305. In many embodiments, block 305 is the manual input (or a database of manual input) from one or more healthcare providers (nurse, doctor) entering the normal expected outcomes of healthcare provisioning with respect to age, gender, or disease against a particular patient profile. A healthcare outcome translation metric is then created for the normal profiles with respect to the age, gender, or disease by using the mapping rule database 206 in step 302. Alternatively, the manual input may be in a numerical format, in which case the mapping rule database is not required. This normal profile is specific for each patient profile.

Figure 5 is an overview flowchart of healthcare provisioning outcomes assessment and figure 6 gives details of its function.

In step 101 of figure 5 the assessment components reads databases, in step 102 it makes the assessment and in step 103 the Q-Score is printed. Turning to figure 6, in step 401 the appropriate formula is read, and in step 402 healthcare outcomes assessment component 102 calculates variation between actual and normal expected healthcare outcomes by using the formula database 405. Database 405 contains formulas for the quality assessment of healthcare provisioning for each particular condition and the stage of healthcare provision (milestone or goal). The healthcare outcomes assessment component 102 then calculates harm of the healthcare provisioning in step 403 by using the actual healthcare outcomes 207 and the harm metric database 406. The database of actual healthcare outcomes, 207, which is an output of figure 3, contains actual healthcare outcomes resulting from the healthcare provisioning. Database 406 contains the metric for harm with negative values. The healthcare outcomes assessment component 102 calculates the quality score (Q-score 309) by adding variation (between actual and normal expected healthcare outcomes) and harm of the healthcare provisioning in step 404. This calculation may be by simple addition. The healthcare outcomes assessment component 102 then outputs Q-score 309, which is the quality score for healthcare provisioning, in step 103.

This Q-score 309 is used by the process manager 100 for evaluating the quality of healthcare provisioning. The tables below give examples of data held in rule database 206 and formula database 405, along with corresponding translation metrics for an actual profile (to be assessed) and for the normal profiles. The rule database 206 contains medical input data including possible negative/harm inputs.

Rule Database 206: an example

where HR == Heart Rate

Formula Database 405: an example

where Fm_a == Actual Face Movement; Fm_n == Normal Face Movement

Am_a == Actual Arm Movement; Am_n == Normal Arm Movement

S_a == Actual Speech; S__n == Normal Speech

Translation Metric for Normal Expected Profiles: an example

Condition I Milestone Age Gender Ethnicity J Days Score

Stroke j Treated 40-45 F British 1 2

I j - T/GB2012/050382

14

Translation Metric for Actual Profiles: an example

Examples of Input to outcome measurement component 200:

Age = = 45; Gender = = F; Ethnicity = = British; Day = = 1 ; Condition

Milestone = = Treated; Parameter ID = = Fm; Text = = "Smiling"

Embodiments of the present invention have numerous technical benefits in the processing of large data quantities efficiently. In particular, computer systems of invention embodiments are faster, efficient and time saving with respect to use of simple database applications. They require less computer power by reducing CPU cycles at the point of use.

Invention embodiments also significantly reduce the frequency and amount of data transmission at the point of use because fewer interactions are required than would be for standard database use. Furthermore the frequency of the amount of data storage at the user point is lowered.

Outcome measurement component 200 enables fewer interactions by translating non- numerical data into numerical data. Component 102 for outcome assessment has several technical advantages. Firstly, it is this component itself which identifies the required parameter(s) for quality assessment, so that the user point (such as an end user's terminal) does not need to send specific requests for parameters on the basis of which the quality score is calculated. Moreover, the outcome assessment component makes use of the result of the outcome measurement component as well as using a database of normal expected healthcare outcomes, a formula database and a harm metric database. Only data required for assessment of the particular condition(s) and milestone(s) are transferred to the healthcare outcome assessor. This is a significant reduction in data transfer over other methodologies.

Fig. 7 is intended to illustrate interactions between the databases and user terminal for a system which does not have the components 200 and 102. The extra interactions (in solid lines) are an overhead on the system. The bold solid lines are the fewer interactions for the proposed system of invention embodiments.

In the absence of measurement and assessment components 200 and 102, the recipient/user end would not only require excessive computing power but also extra storage to save intermediate data generated as a result of the internal processing. Moreover, most of the logical processing would take place at the user side and that would require more computing power.

In figure 7, the components already introduced in the previous figures are shown for one particular application. The figure also includes a local repository for local data storage. In a possible related art implementation of a method of quality assessment without the outcomes measurement component 200 and outcomes assessment component 102, databases 204, 208, 205, 303 and 406 are available, but the mapping rule database 206 and formula database 405 are not. In the related art comparative example, the exchange of information between the user point represented by the process manager 100 and the database applications replacing the measurement and assessment components involves multiple exchanges. In contrast, the "intelligence" in the measurement and assessment components allows a simple query to be sent from the process manager to the assessment component with a simple response in numerical form only from the assessment component to the process manager.

The system interactions shown in Fig. 7 are for one stroke patient (Disease = = Stroke) under treatment (Goal = = Treated) with one parameter ID (FM = = Face Movement). The need to avoid excessive use of computing power and storage resource is magnified if the method/mechanism needs to be repeated for more than one parameter IDs or for multiple patients within a population. For example, if the quality of treatment is evaluated for one region with multiple hospitals and numerous patients, then the number of interactions for a simple database implementation (in terms of transmission of data) would be enormous with a requirement of massive data storage and computing power. Figure 8 represents the hardware implementation of the computer system of invention embodiments. A healthcare process manager or other user is provided with a hand held terminal computer including the process manager 100. The skilled reader will appreciate that the computing device which provides the process manager may be of any suitable type, such as a PC, tablet PC, laptop PC, PDA or other such device. This terminal computer is connected via a network such as a wide area network to a server which provides the functionality of the measurement and assessment components. Also housed within this computer are the mapping rule database, actual healthcare outcomes and formula database as previously described. The server is connected via networks such as a wide area network to a database server which accepts manual input 205 and provides the two direct data databases 204 and 208 as previously described, the normal expected healthcare outcomes database 303 as previously described and the harm metric database 406 as previously described. Figure 9 shows various scenarios in which the computer system of the embodiments can be integrated and illustrates the sheer volume of data available for processing. Data from the patient's home, hospitals, a nursing home, a clinic and insurance companies is fed to a quality assessment service. The quality assessment service of invention embodiments (referred to as HOME for Healthcare Outcomes Monitoring sErvice) is used in four or more different scenarios: Ward Round, A&E, Government Analysis and Retail Health. For these scenarios a number of user interfaces can be provided, according to the healthcare experts involved.

Figure 10 illustrates levels of comparison provided by invention embodiments. The results to be assessed can be at individual level (one or more individuals) or at institutional level (part of an institution, all of an institution or a group of institutions.

Figure 1 1 includes two graphs, for Hospital A and Hospital B. Hospital A has a higher mortality than hospital A for diabetic patients and the mortality rate has been traced to insulin dosage using invention embodiments. The consultant, Hospital Manager and Regional Director of Healthcare can all benefit from this information.

Figure 12 is an "Episode Tree" illustrating the Goals (or Milestones) in an illness/wellness cycle for a particular condition and how the goals are measured, resulting in a Q-Score. The milestones M1 -M7 are indicative of some of the events which may be selected for a given condition, but these could change or new ones could be added depending on the condition (or medical opinion). In summary, invention embodiments provide an efficient quality audit and evaluation system for healthcare use.

Invention embodiments allow enhancement of assessment of healthcare provision quality. The method and system is capable of acquiring data from databases (204, 205, 208, 305, or 406) automatically and calculating the quality score in a way that would aid healthcare stakeholders to evaluate the quality of healthcare provision by various providers.

Invention embodiments can provide a means to evaluate the quality score of healthcare provisions against each milestone within a condition. The outcome measurement component and outcome assessment component can be individually enhanced or updated for each new condition and milestone; although the number of conditions is massive, the invention embodiments reduce the overhead of updates and enhancements.

The described method and system to assess the quality of healthcare provisioning use the outcome-centric approach and perform outcome assessment. Thus the clinical outcome of a clinical process is used to measure the quality of that process. The output (result) of the system mentioned may be a so-called Q-score that is a measure of healthcare provision quality. This Q-score can be used by the process manager, as an outcome quality indicator, in order to analyse and improve the healthcare processes. The system may be able to identify within a clinical process 'what went wrong' and 'where'. For example, if a patient's health deteriorated due to an inaccurate diagnosis or an inappropriate treatment performed by the doctor this can be pinpointed.

The method and system can be used to carry out the audit, evaluation, and/or management of quality of healthcare provision in hospitals and the community. They can provide effective auditing of quality of healthcare delivery through the auditing and evaluation of the quality of outcome. They can achieve improved quality of healthcare delivery through the implementation of quality assessment, evaluation of clinical outcomes, and facilitating evidence-based medicine. They can reduce the cost of healthcare provision caused by low quality provision, e.g. inaccurate diagnoses or inappropriate treatments.