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Your Clinical Outcomes

The eye care industry’s leading software designed to
extract and analyze clinical outcomes from your EHR.

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Our Most Popular Registries

Diabetes Management Registry Click for details...

This registry will enhance you care of diabetic patients by monitoring
HbA1c change and predicting the advent of a retinopathy.
Reports will help you build referrals from other physicians.
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Cataract Extraction Registry Click for details...

Surgical outcome reports will help you decide which surgeons, surgical procedures and IOL types are producing the best outcomes. You will be able to compare your results with other surgeons in your practice or other surgical practices.
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Dry Eye Registry Click for details...

This registry will guide you in prescribing the most effective treatment modalities for specific types of dry eye patients.
In addition to helping you reduce attrition, you can use the registry to demonstrate to PCPs the need to refer patient with dry eye symptoms.
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Myopia Registry Click for details...

Data driven reports from this registry, will guide you in prescribing the most efficacious modality of myopia management for each individual patient. You can also use this data as a tool to educate your patients, parents, educators and to market your practice.
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OrthoK Registry Click for details...

HealthCare Registries can provide you with “real-time” clinical outcome data to help guide you in prescribing the most effective treatment to slow elongation.  The data can also be used to enhance the financial viability of your practice by identifying attrition issues.
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Diabetes Management Registry
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Problems:
  1. Providers do not have data regarding the number of with Diabeties Type 1 or Type 2.
  2. Providers do not have data regarding the number of patients with Diabetic Retinopathy.
  3. Providers do not have data regarding the number of patients with a validated HbA1c.
  4. Providers do not have data regarding HbA1c change for better, stable or worse.
  5. Providers do not have access to the % of patients in each HbA1c category and yearly change.
  6. Providers do not have a method of comparing their management of diabetes with other practices.
Purpose:
  1. To provide essential data to providers regarding their diabetic patients.
  2. To provide practitioners with data to better manage their diabetic patients.
  3. To provide practitioner with Diabeties data to share with PCPs.
Goals:
  1. To use outcome-based data to monitor the HbA1c of their diabetic patients.
  2. To use data from a practitioner’s EHR to compare their outcomes to other practitioners.
  3. To provide outcome-based data to help build referrals.
Strategy:
  1. Record and track clinical outcome data on all patients.
  2. Record and track patient attributes and treatment modality aimed at improving outcomes.
  3. Record and track treatment outcomes as a reference and a metric for rating performance efficiency.
Cataract Extraction Registry
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Problems:
  1. ODs who co-manage post-operative cataract extractions often fail to send their progress reports to the Ophthalmologist. Reports that are faxed are problematic which hinders MIPS reporting.
  2. In group Ophthalmology practices, there are considerable differences as tothe surgery type and IOL style. Many of these decisions are based on unrelated factors.
  3. There is significant variation from practice to practice in the percentage ofspecialty implants used. Patient satisfaction data is usually lacking to assess the percentage of patients who received the most appropriate lens style. Data correlating objective results and patient satisfaction is rarely available, which should be driving the decision-making process.
Purpose:
  1. Provide data as to the number of cases that co-management reports havebeen received and provide a list of those still needing post-op reports.
  2. Provide clinical outcome data on cataract surgery based on surgicalprocedure, type of lens implant, and surgeon. Provide outcomes data that help providers understand the influence of Social Determinants of Health,(SDOH) factors on care outcomes, especially in regard to the number of specialty implants prescribed.
  3. Provide data showing the effect on patient choice to select a specialty implant based on when the concept is introduced to the patient.
Goals:
  1. Clinical managers will have a more simplified method to make sure all post-opreports are received. ASOA will work with EHR vendors towards full automation.
  2. Surgeons will have clinical outcomes data to help them decide which procedures, implants, and products result in the best patient outcomes from both an object standpoint of clinical findings as well as subjective results based on patient satisfaction.
  3. Referring ODs will understand how their referrals and handling of specialty implants affect outcomes. 
Strategy:
  1. Continue to expand cataract extraction analytics based on user requests
  2. Add the ability to get patient satisfaction results
  3. MaxMD partnership
  4. Expansion of website
  5. Integration with EHRs patient portal
Dry Eye Registry
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Problems:
  1. Dry eye treatments by eye care providers tend to be arbitrary or at the whim of the provider. 
  2. Eye care providers, with no consideration of meibomian gland dropout, tend to treat patients presenting with dry eye symptoms with OTC lubricants. 
  3. Eye care providers have no way to compare their dry eye treatment results with those of other providers.
  4. Most providers have no idea as to attrition rate of their dry eye patients
Purpose:
  1. Define the most effective treatment modalities for specific types of dry eye patients. 
  2. Create data that demonstrates to primary care physicians the need to refer patients with dry eye symptoms.
  3. Provide comparison dry eye treatment data with other providers
  4. Provide appropriate attrition data on dry eye patients
Goals:
  1. To provide registry users with better guidance as to which treatments work most effectively for each population of dry eye patients.
  2. To provide registry users with access to data to help educate primary care physicians and build referrals for dry eye patients.
  3. To provide registry users with access to data that allows them to see how their dry eye treatment results compare to other providers
  4. To provide registry users with access to data to help reduce attrition of dry eye patients
Strategy:
  1. Track dye eye treatment results to advance knowledge of which treatment modalities are more effective.
  2. Track data to demonstrate to primary care physicians the need to identify and refer dry eye patients
  3. Create data to show the percentage of patients with early dry eye symptoms with meibomian gland dropout who should be prescribed more aggressive therapy.
  4. Capture meibography images to compare normal vs significant dropout of meibomian glands.
  5. Provide meibography images to Health Information Exchanges (HIE) to establish the value of sharing data with The Healthcare Registries
  6. Use meibography images to educate local physicians on identifying practitioners who provide dry eye services
  7. Retrieve data from HIEs to show the number of patients diagnosed and treated for dry eye by primary care physicians.
Myopia Registry
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Problems: 
  1. Providers do not have data as to the prevalence and degree of myopia in their patient population. They currently rely on Asian populations studies which were done in Asia.
  2. Providers do not have a method of comparing the age of myopia onset and rate of myopia progression in their practice as compared to other practices.
  3. Providers do not have local community data to educate their patients and educators.
  4. Providers do not have data to compare the effectiveness of the various treatment options.
Purpose:
  1. To provide practitioners with the data as to the prevalence and degree of myopia of patients in their practice.
  2. To provide practitioners with the data as to efficacy of various modalities on slowing the progression of axial elongation.
  3. To provide feedback on the treatment and referrals related to myopia education.
Goals:
  1. To use outcome-based data to prescribe the most efficacious modality of myopia management for each patient.
  2. To use data from a practitioner’s EHR to compare their outcomes to other practitioners.
  3. To provide treatment data to providers to be used to educate patients, parents, teachers and educators. To make them aware that the decisions they make may impact the risk of a child developing of myopia.
Strategy: 
  1. Record and track refractive data on all patients
  2. Record and track patient attributes and treatment modality aimed at slowing axial elongation.
  3. Record and track treatment outcomes as a reference and a metric for rating performance efficiency.
OrthoK Registry
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Problems:
  1. Providers do not have data on OrthoK efficacy on slowing axial elongation from their patient population. They currently rely on studies done on Asian populations in Asia.
  2. Providers have no mechanism to compare visual quality, patient satisfaction, impact on vision-related quality of life or efficacy of slowing axial elongation in their practice compared to other practices.
  3. Providers do not appreciate the potential income that an OrthoK patient can bring to their practice.
Purpose:
  1. To provide data on efficacy of OrthoK (compared to other modalities) on slowing of axial elongation in their patient population.
  2. To Provide data on visual acuity, patient satisfaction, vision-related quality of life and efficacy of slowing axial elongation with OrthoK in their practice compared to other practices.
  3. To provide data on patient retention/attrition with OrthoK.
Goals:
  1. To use outcome-based data to prescribe the most efficacious OrthoK design.
  2. To use data from a practitioner’s EHR to compare OrthoK outcomes vs. other practices.
  3. To use attrition data to retain OrthoK patients and demonstrate its overall benefits to your patients and practice.
Strategy:
  1. Record and track OrthoK patient details and treatment attributes relative to axial length and mode of treatment.
  2. Record and track OrthoK patient treatment outcomes as a reference and a metric for rating performance efficiency.
  3. Track OrthoK patient visit frequency vs. recommended return date.
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