Table 4 Emerging themes from primary care providers and specialists

GENERAL IMPRESSIONS

Wait time data is viewed positively by primary care providers (PCPs^a) and is seen to have value

1. Official registry/access to specialist wait time data seen as very useful

Specialists have interest in wait time data

1. Some clinics/specialists have never seen their own data or that or colleagues

2. Website with specialist by region, updated every month by clinics/specialist seen as useful particularly for PCPs

CLINICAL UTILITY

Majority of primary care providers perceive wait time data to have significant clinical utility

• Knowledge of wait-times increases PCP (& patient) specialist choices

• Choosing specialist within closest geographical convenience for patient

• Choosing specialist with shortest wait times

• Helps to manage patient expectations

• Useful for improving patient care

• Useful for urgent referrals

• Potentially increases patients’ timely access to care—patients don’t have to suffer unnecessarily for long periods

There was variable perception about` the clinical utility of wait time data for specialists

1. Review of data may lead to clinical improvements

• Provides feedback and could reveal inefficiencies rather than capacity issues which would allow for redistribution of resources for some specialties

• If specialists are aware of data they may be motivated to find resolutions (competitive response)

• Would allow specialists to provide alternatives for patients when full

• No standardization exists to triaging patients, therefore a review of the triage practices of those specialists with shorter wait times could be helpful for all

2. Review of data has little or no impact/clinical utility for clinics/specialists

• Even if aware, specialists may not be able to change wait times (e.g. Surgeons are limited by how may surgeries they can perform per day)

• Data would not change practice or how patients are booked

• Some data (e.g. surgical oncology) already exists at system level yet no changes have been effected, thus specialists question impact of additional data

PERCEIVED BENEFITS & VALUE OF DATA

Data is perceived to have value for both PCPs and specialists because it increases awareness

1. Data increases PCP access to knowledge & information regarding specialists (SPs)

• Some PCPs currently find specialists by informal methods i.e. asking colleagues who they refer to or asking patients who they friends have been referred to – official registry is useful to have

• Useful resource when new to the city or newer to practice

• Organized & accessible—some PCPs are currently find specialists via ad hoc means, i.e. asking colleagues who they refer to or patients who they friends have been referred to

2. Data allows specialists/clinics to become aware of their own wait times

• If specialists are aware of data they may find internal resolutions or workarounds

• Acknowledgement that specialists may not be able to change wait times even with greater awareness

Wait time data has systemic relevance

1. Relevance is seen for local, regional and provincial administration bodies (department chiefs, hospital CEOs, standards committees, LHINs^b, HQO^c)

2. Provincial wait time data would highlight inequality in Ontario which may lead to improvements

Data increases awareness—availability of data allows specialists/clinics to become aware of their own wait times

1. Urgent wait times are often of importance to specialists because of targets set by clinic – most specialists don’t know if they are meeting these

2. Data may highlight disconnect between perception (self-reported wait times) and reality

3. Sub-specialization wait time data provides more detail of where bottlenecks might be

4. Data provides a comparator with other specialties in region even if clinics/specialists are limited in resolutions

5. Valuable information, particularly for non-surgical specialists (e.g. Ortho surgeons have Wait 1 & 2 Data provincially monitored and sent back—non surgical ortho data may be lacking)

The systemic relevance of additional wait time data is not clear for all specialists

1. Some data (e.g. surgical/oncology) already exists at system level, yet no changes have been effected, thus specialists question the impact of additional data

2. Some specialists acknowledge systemic relevance for department chiefs, hospital CEOs, standards committees LHINs and administrative bodies such as HQO

• Primarily useful for department chiefs with regards to bottleneck identification

PERCEIVED CHALLENGES/LIMITATIONS

Data does not provide information related to quality of referral and variances in wait times

1. Quality or cannot be discerned

2. Data provides no contextual information which may account for outliers

Wait time data may not change referral patterns—some PCPs report having “favourites” who they already refer to and accessing wait time data may be

There may be unintended consequence of making data available

1. Wait times for some specialists could increase if a real-time or a dynamic, updatable interface is not embedded in the design

2. Alienation of some specialists, particularly those with longer wait times

Data does not reflect variance with regards to referrals

1. Factors influencing referrals and wait time data include

• Patient preference

• PCP preference

• Type of problem or diagnosis

• Appropriateness/quality of referral

RECOMMENDATIONS

Presentation of wait time data for PCPs can be improved by increasing clarity, accessibility and user friendliness for PCPs

1. Increase clarity

• Group data for easier or quicker identification e.g. wait times below or above 50 days

• Cluster by sub-specialty (e.g. separate ob & gyn wait times as difference exists)

2. Sort data by shortest wait times and/or geography

3. Provide filters (i.e. if platform is interactive) so PCPs can choose specialist based on own criteria (e.g. geography, affiliation, urgent/non urgent referral etc.) which may change case by case

4. PCPs prefer data to be made available to them via easy to access means

• Link in the EMR

• Email

• Easy access at point of care important

Wait time data that is updated regularly is seen as important

1. Real time interface and updates if possible was seen as ideal

2. The most popular interval for receiving updates was quarterly followed by every 6 months

3. An opt out option for PCPs who no longer wish to receive updates is important

Although benchmarks are key for establishing a standard of care, setting these for specialist referrals may be controversial & challenging to achieve

1. Benchmarks may be unrealistic

• May be unrealistic because of geography and location of specialists—may set up unreasonable expectation

• There are too many specialties & sub-specialties for benchmarks

• Specialists in Ontario are at capacity so they can’t accommodate patients any faster

2. Benchmarks may inherently place judgement, blame & stress on specialists

3. Rather than benchmarks, it is better to look at similar healthcare systems doing better and find ways of mirroring or learning from them

Public reporting of wait times may be inevitable in the future but may cause challenges (e.g. patients wanting to choose a different specialist than recommended) and further strain the health care system

For next steps, consider an implementation trial exploring actual utility of wait time date by PCPs and also patient behavior

Additional, more robust data may be of interest to both specialists and PCPs

1. Contextualized comparison data (to help explain anomalies or outliers) is important

2. Data should include communication wait times from specialist to PCP (i.e. letter from specialist to PCP) as this is important for adhering to standards

3. Including the type of referrals accepted by may be educational for PCPs

Quarterly updates of accessible wait time data could allow specialists to review and plan

1. Nominal reporting should be by group/clinic consensus

2. Data should be easily accessible e.g. email or presentation in specialty group meeting

3. Platforms with access barriers e.g. passwords would prevent or limit use of information

Mixed views exist about establishing benchmarks

1. While benchmarks are seen by some as arbitrary because they depend on sub-specialty or diagnosis, they are also seen as important for setting standards and improving healthcare systems

Public availability all wait time data is OK (and some exists already but should include education for patients so the public better understands clinic variances

Next steps

1. Consider a block randomization trial—releasing data to a few to see if this has impact on actual wait time

2. Evaluation of what constitutes urgent referrals are needed as PCPs have a low criteria for “urgent”

• Important for PCPs to ask the right questions and know when referral is valid—impacts wait times