Introduction

In the developed world there is a ‘Quality Chasm’ between the quality of care that can be achieved and the quality and consistency of care that is being delivered. Several types of quality problems have been documented including, undue variation within services, underuse of services, overuse of services, misuse of services, and regional or ethnic disparities. Health care’s problems with safety and quality are often because it relies on outdated systems of work. Only by re-designing systems of care including the use of information technology and automated decision support will consistently improved quality of care be delivered. Both in the United States of America (USA)1 and in the United Kingdom (UK)2 major reports have highlighted these problems and charted a route to higher quality health care in the future.

These reports defined the aims for health care systems as providing safe, effective, patient-centered, timely treatment and doing so efficiently and equitably. The design principles for achieving this include: continuous relationships, evidence-based decision making, customization based on patient need, patient control, shared knowledge, and safety as a system property. In addition the health system should not waste resources or patients’ time and clinicians and institutions must cooperate and communicate to share appropriate information.

The focus of medical training has traditionally been on the central role of the doctor–patient relationship. There has been a lack of attention on the system infrastructure that supports that relationship and informs correct decision making. Each group of health care staff is typically trained separately and this can compromise the effectiveness of teams and slow the changes in roles that are needed as practice changes.

It is widely recognized that individuals and organizations can only improve performance by incorporating measures of processes and outcomes into daily work.

Defining what data needs to be collected and how this should be used and shared is therefore at the heart of high quality health care.

Cataract surgery – do we have a high quality system?

Do the above general comments on health care apply to assessment and surgery of patients with cataracts?

The vast majority of ophthalmologists and their staff in the USA, UK, and other developed countries still use paper records. This means that vital health information is poorly organized, inconsistently recorded, and often illegible. Data cannot be easily retrieved or shared in a timely fashion and it is enormously time consuming or impossible to aggregate data from multiple patients to audit the outcome of surgery. As a consequence few surgeons have a detailed understanding of their successes or complications and how they are performing relative to their peers or benchmark standards published in the literature.

Such lack of knowledge of clinical outcomes and care processes inevitably means that the quality of cataract surgery is lower than it otherwise could be. It can therefore be concluded that on a population basis the provision of cataract surgery suffers from the same failings identified for the whole health care system.

Within the limitations of paper records some of these issues have been addressed by the development of ‘cataract care-pathway documents’ that encourage, but cannot enforce, recording of all data relevant to the preoperative assessment, anesthetic, surgery, and postoperative care of patients in a more structured way. Patient safety and consistency of care is improved but it is still impossible to aggregate data easily. The process of recording clinical data is still repetitive and does not automatically ‘learn’ from previously recorded information.

Cataract surgery – how should data be collected?

Many of the above problems can be solved by implementing specialty-specific electronic medical record (EMR) systems that mandate appropriate data collection at every step of the patient care pathway. The ability to audit clinical practice as an automatic by-product of routine clinical care and decision support functions specific to ophthalmology are frequently missing from multi-specialty EMR systems, hence just because a hospital or clinic has implemented EMR does not imply that the quality of care has necessarily been improved.

To deliver detailed audit of clinical outcomes on a regional or national basis requires aggregation of data from multiple EMR systems. The datasets that are collected need to be standardized across health care providers to allow fair comparison between individuals and institutions. For ethical and privacy reasons it is usually necessary to pseudoanonymize the data such that no patient is identifiable.

Alternatives to EMR systems for aggregating clinical process and outcomes data are national or international registries. Sweden led the way with an active National Cataract Register that has been able to identify changing trends since 19923. Initially data were submitted on paper proformas but web-based data entry is now the norm. The European Society of Cataract and Refractive Surgery has recently been funded to establish a pan-European registry with web-based data entry4. Whilst registries are welcome there are limited mechanisms to guarantee the accuracy of data or to determine what cases have been omitted. The work involved in entering data into a web-based registry is always additional to the work involved in hand writing the paper notes or entering data into local EMR systems, which limits the volume and detail of data that can be collected.

Cataract surgery – what data should be collected?

When designing the ideal cataract care pathway within a health care system to support the aims defined in the introduction to this chapter it is important to start at the most granular level by defining every element of data that is needed at each stage of the care pathway. This ‘Cataract Dataset’ should be designed to include all data items that both are required to support best clinical practice and are needed to allow detailed audit of clinical outcomes, whilst taking due account of case mix to allow fair institutional and clinician comparison.

The UK has had a formal national process involving all relevant stakeholders to define the ‘Cataract National Dataset’ (CND)5. When this is ratified it will be a standard to which all EMR suppliers to the UK National Health Service (NHS) must conform. The UK CND represents the most detailed definition of data collection for cataract surgery in the world and numerous peer reviewed publications have demonstrated that it is fit for purpose in allowing detailed audit of the process and outcome of care as a by-product of routine clinical care6–8. Almost a third of the 300 000 cataract operations performed per annum in the NHS in England are now recorded within EMR systems from the same supplier, but each hospital has a separate instance of the program. To date there has been no automatic mechanism for aggregating pseudoanonymized data from all sites but a National Ophthalmology Database is being established for this purpose.

The detail of data collection defined in the CND is possible only within EMR systems that have been specifically designed to meet the particular needs of ophthalmology.

Cataract surgery – how should the data be used?

Once high quality data are being routinely collected within EMR systems there will be a multiplicity of uses for this data, several examples of which are given below.

Accreditation, regulation, and revalidation

In some health economies clinicians are required by regulators to audit their clinical outcomes and demonstrate their continued fitness to practice. Numerous clinical studies document ‘mean’ outcomes, but very few studies analyse variations in clinical outcomes between surgeons or institutions, whilst taking due account of case mix. This is necessary if acceptable boundaries of performance are to be scientifically defined without the risk of making surgeons averse to operating on complex cases. Posterior capsular rupture rates between surgeons of different grades have been published for a dataset of 55 567 cataract operations7 (Fig. 20.1) and future publications will adjust each surgeon’s rate according to their case mix complexity using a statistical process control chart (or funnel plot) to identify outliers.

Fig. 20.1 Funnel plot for all surgeons: percentage of operations complicated by PCR vs. number of operations performed by each surgeon. (Data for eight surgeons with PCR in 20% or more of their operations (range 20–100%) are not shown). These surgeons had contributed between 1 and 29 operations to the dataset and all were trainees.) (N = 406 surgeons.) Overall PCR rate = 1.92%.

From: RL Johnston, H Taylor, R Smith, et al. The Cataract National Dataset Electronic Multi-centre Audit of 55,567 Operations: variation in posterior capsule rupture rates between surgeons. Eye advance online publication 14 August 2009. Reproduced with permission from Nature Publishing Group.

Cataract surgery – making quality improvements happen

Despite the increasing focus on the quality of health care too little attention has been paid to analysis and alignment of payment incentives with quality improvement. For example in a fee for service system there is a financial incentive to doctors to perform too many operations.

In the USA the Centers for Medicare and Medicaid Services created the Physician Quality Reporting Initiative to give financial incentives to clinicians who return specified data items.

Summary

Carefully designed, evidence-based cataract care pathways, supported by specialty-specific electronic medical record systems that automate clinical information and provide decision support, offer the greatest promise of achieving consistently high quality cataract care for all.