Ultimate Blogging Championship

Tag: Members Only

  • Reasonable wait for appointment – D2D 3.0

    Click on the following links to access: 1. Technical notes 2. Interpretive notes 3. Data quality actions – Actions and ideas to consider and discuss with clinical leads and other members of the team 4. Potential actions related to processes of care – Actions and ideas to consider and discuss with clinical leads and other members of the team

  • Patient satisfaction with office staff – D2D 3.0

    Click on the following links to access: 1. Technical notes 2. Interpretive notes 3. Data quality actions – Actions and ideas to consider and discuss with clinical leads and other members of the team 4. Potential actions related to processes of care – Actions and ideas to consider and discuss with clinical leads and other members of the team

  • Patient experience: involved – D2D 3.0

    Click on the following links to access: 1. Technical notes 2. Interpretive notes 3. Data quality actions – Actions and ideas to consider and discuss with clinical leads and other members of the team 4. Potential actions related to processes of care – Actions and ideas to consider and discuss with clinical leads and other members of the team  

  • Same/Next Day Appointments – D2D 3.0

    Click on the following links to access: 1. Technical notes 2. Interpretive notes 3. Data quality actions – Actions and ideas to consider and discuss with clinical leads and other members of the team 4. Potential actions related to processes of care – Actions and ideas to consider and discuss with clinical leads and other members of the team

  • EMR Queries for D2D – Diabetes Care Composite Indicator

    The queries below were developed by QIDSS and the EMR Communities of Practice. They will help you extract data to monitor diabetes care, and they can also help you prepare the data for submission to D2D.

     

    Why Diabetes?

    There are two reasons to include a diabetes care indicator in D2D. The main reason is to include clinical data in primary care performance measurement, especially considering clinical care remains the core business of AFHTO members. Another reason is the need to show the value of team-based care. EMRs are the only repository of data created and used by teams and therefore are the best source of data to reflect the contribution of the entire team to patient care. As well, EMRs are the most up-to-date source of data about the whole person available in primary care.

    A composite indicator

    Following the lead of the EMRALD project, the 4 measures used in the diabetes numerator (HbA1C testing done at appropriate interval and appropriate levels of most recent HbA1C, blood pressure, and cardiovascular protection via statin therapy) will be combined into a single composite indicator for diabetic performance. If you want to start monitoring your diabetes care we have a process to help you. This involves running a standard query to identify your diabetic population and cleaning your EMR by coding those patients accordingly. Check out the suggestions on the “Getting started on a diabetes registry” webpage or contact improve@afhto.ca for more information. Please refer to the EMR-specific instructions below to generate data for the Diabetes Care indicator. Once you have tried running these queries, consider sharing your challenges and successes with your EMR CoP or contact us so we can all get better at doing this!

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data. Please exercise judgement when using them, as they are meant to support and complement a chart review, not to replace it.

    Telus PS 

    CODED: If your diabetic patients are coded with ICD-9, ICD-10, or SNOMED CT – use the D2D Diabetes Care v1 searches (.srx files) to generate data for the diabetes composite indicator. They run quickly! Screenshots of the numerator searches and denominator search can be found in the guide. UNCODED: If you are not sure how your team codes patients with diabetes in your EMR, please use the D2D Diabetes Care uncoded v1 searches (.srx files). They will extract data for all patients identified with diabetes, based on the case definition developed by CPCSSN and translated for EMR use by the QIDSS Algorithm Project. Beware, these comprehensive searches may take a while to run! Screenshots of the numerator searches and denominator search can be found in the guide. Save the searches to your desktop and import them into your EMR. After running the searches, take the list of unique patient ids resulting from each of the 3 numerator searches and the denominator search. Plug these numbers into the Diabetes Care Calculator to generate the composite score for your team. This score is the number to be entered into the D2D submission platform. You might need the help of your QIDSS, IT staff or other person who usually runs queries in your EMR. Consider sharing your challenges and successes with the Telus PS CoP or contact us for more information.

    Accuro 

    CODED: If your patients with diabetes are coded with ICD-9 250 use the 4 queries (D2D- Diabetes Care v1) located on publisher to generate data for the diabetes composite indicator. Once the queries are run, import the patient lists (PHNs) into the Diabetes Care Calculator. You may need the help of your QIDSS, IT staff or any other person who usually runs queries in your EMR. Consider sharing your challenges and with the Accuro CoP or contact us for more information.

    Nightingale 

    CODED: If your patients with diabetes are coded with ICD-9 250 please use the queries illustrated in the links below to generate data for the diabetes composite indicator. Please review this guide before proceeding – it contains instructions and options for calculating your diabetes care score. If you choose to use the Diabetes Care Calculator there are a number of steps involved but it will calculate the diabetes score for you.

    You may need the help of your QIDSS, IT staff or any other person who usually runs queries in your EMR. Contact us for more information.

    OSCAR 

    CODED: Please review this guide before proceeding – it contains screenshots of the reports. If your patients with diabetes are coded with ICD-9 250 – please use the D2D Diabetes Care v2 queries to generate data for the diabetes composite indicator. Two sets of queries were created as a result of query run time issues. The following set of queries search for diabetic patients for all physicians. If you experience excessive query run time you can use the queries that run for each physician. Once the queries are run, import the list of unique patient id’s from each report into the Diabetes Care Calculator. Although a number of steps are involved, it will calculate the diabetes score for you. Consider sharing your challenges and successes with the OSCAR CoP or contact us for more information.

    P&P 

    NOTE: we are unable to create a query for blood pressure due to global data restrictions. The vendor expects a fix to be deployed with the next release. We will post a query as soon as this issue is resolved. We do have 3 other queries (HBA1c testing, HBA1c levels, and Statin) that you can run to start building the composite indicator, as below. Please download the D2D Diabetes Care v1 queries for the diabetes indicator. The numerator queries are based on patients being coded using ENCODE-FM (ICD9  = 250). The denominator query is based on the CPCSSN case definition and will help you identify patients with diabetes who might not be coded in your EMR. Due to the way the lab results are handled in P&P, the report generated by the numerator queries will need to be exported to excel and filtered to find most recent A1c values and dates. Please see screenshots in this guide for reference. Once the queries are run, import the patient lists (unique IDs only) into the Diabetes Care Calculator. Although a number of steps are involved, it will calculate the diabetes score for you. You might need the help of your QIDSS, IT staff or other person who usually runs queries in your EMR to import and execute this query. Please consider sharing your challenges and successes with the P&P CoP or contact us for more information.  

  • EMR queries for D2D – EMR Data Quality: Smoking Status Complete

    Please find below EMR queries developed by QIDSS and the EMR Communities of Practice that will help you extract data for submission to D2D.

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data.

      Once you have tried running these queries consider sharing your challenges and success stories with your EMR CoP or with us so that others can benefit from improved and shared solutions!

    Telus PS (Note – There are issues with queries developed in previous versions of PS. We are in the process of updating the queries and will be available at the launch of D2D (August 21, 2017)

    The D2D EMR Data Quality Smoking Status v1.1.1 searches (.srx files) will extract data for the numerator and denominator for all patients (>=12 yrs) who have smoking status documented in the risk factors module. Save these searches to your desktop and import into your EMR. You might need the help of your QIDSS, IT staff or other person who usually run queries in your EMR. Instructions on how to import the searches into your EMR can be found in this guide. Share you challenges and successes with the Telus PS CoP or contact us for more information.

    Accuro 

    Please find the D2D EMR Data Quality Smoking Status v1 numerator and denominator queries on Publisher. Query criteria and instructions on how to generate rate data for the smoking status complete measure can be found in this guide. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share you challenges and successes with the Accuro CoP or contact us for more information.

    Nightingale 

    Instructions on how to build and run a query in Data Miner to generate data for the smoking status complete measure can be found in this guide. Contact us to share you challenges and successes.

    OSCAR 

    Download the D2D EMR Data Quality Smoking Status v1 query to your computer and import into your EMR. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share you challenges and successes with the OSCAR CoP or contact us for more information.

    P&P 

    The P&P Smoking Status Query v1 file (.dat file) includes the numerator and denominator queries that will help you generate data for all patients >=12 yrs old with smoking status documented in Risk Factors. The data field used in the numerator query is a “learning field” and may need to be customized depending on how your team documents smoking status. You might need the help of your QIDSS, IT staff or other person who usually run queries in your EMR to import and run this query. Share your challenges and successes with the P&P CoP or contact us for more information.

  • EMR queries for D2D – Patients served

    The EMR queries below were developed by QIDSS and the EMR Communities of Practice to help you prepare data for D2D submission.

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data. 

      This indicator is intended to reflect the ENTIRE patient population served by a team, not just those who are rostered to the team. The definition is “the number of unique patients with a visit (i.e. appointment) to anyone in the team in the last 3 years”. This definition will continue to evolve in subsequent iterations of D2D as EMRs are increasingly capable of recording other meaningful patient encounters (e.g. phone calls) in a way that the data can easily be extracted. For D2D 4.0 the technical limitations of data extraction from EMRs dictate that only in-person encounters can be included in the definition.

    Telus PS 

    The D2D- Patients Served v1 search looks at unique patients with an appointment in the last 3 years. Save the search to your desktop and import into your EMR. You might need the help of your QIDSS, IT staff or other person who usually runs queries in your EMR. Consider sharing your challenges and successes with the Telus PS CoP or contact us for more information.

    Accuro 

    Please download the D2D- Patients Served v1 query from the publisher. The query returns patients with an appointment in the last 3 years and filters out “no shows”. You may need the help of your QIDSS, IT staff or any other person who usually runs queries in your EMR. Consider sharing your challenges and successes with the Accuro CoP or contact us for more information.

    Nightingale 

    Please use this guide to extract data for the patients served indicator using data miner. If you have any questions or would like training on data miner, contact us for more information.

    OSCAR 

    Please save the D2D- Patients Served v1 query to your computer. Here is a guide for importing the query and using the report generated by the query. Consider sharing your challenges and successes running this query with the OSCAR CoP or contact us for more information.

    P&P 

    Thanks to efforts of the CoP an approach to accessing appointment data (i.e “date last seen”) has been programmed by the vendor. It’s called the Patient Utilization Report. This guide will show you how to access the report in the EMR. Please connect with the P&P CoP or contact us for more information.

  • Building Collaboration: Case Study based on QIDS Partnerships

    Patients First calls for collaboration across subLHIN regions. It also calls for spreading measurement for quality improvement and performance monitoring. AFHTO members’ experience in building QIDS partnerships (about 150 AFHTO member organizations are actively involved) provides a foundation for both these objectives. These QIDS partnerships have been a critical ingredient in the advances AFHTO members are making to meaningfully measure primary care. This new resource – Building Collaboration and Increased Capacity through QIDS Partnerships – illustrates three different approaches to organizing these partnerships. It describes each approach and then examines all three to identify the challenges they faced, the enablers for success and the lessons learned. This knowledge, together with that gained from other types of partnerships AFHTO members have developed, can be applied to strengthen your QIDS partnership, evaluate existing partnerships (e.g. Health Links and other community programs) and help to broaden your reach into other areas of collaboration. Learning from your peers: additional case studies AFHTO has developed a series of case studies for our members to share the experience of colleagues on topics identified as being important to you:

  • Case Study: Learning about unionization from ten FHTs

    About 25 FHTs across the province have unionized workplaces. AFHTO, in partnership with the Osborne Group, has prepared a case study for AFHTO members which looks at the advice and learnings from 10 of these FHTs. Even with the anticipated increase in funding, compensation in primary care will remain below market comparators, and so the potential for further unionization remains. Primary care leaders may wish to think about how to prepare for the possibility of union organizing efforts in their FHT or NPLC. The case study documents motivators for union drives and what teams went through in the process of union certification, negotiation and managing in a unionized environment. Importantly, the experience of these 10 teams highlights both the challenges and possible benefits of working under a Collective Agreement. The case study may assist other FHTs/NPLCs as they contemplate the potential for, and the implications of, unionization in their own workplaces. Because of the sensitive nature of some of the information that was provided to us, we have not identified the FHTs by name. However, if any primary health care teams are interested in speaking directly to the Executive Directors or Boards of these FHTs, AFHTO will facilitate an introduction. Case Study: Unionization – The Experience of Ten Family Health Teams [PDF]

    Toward a Primary Care Recruitment and Retention Strategy for Ontario

    The increase in funding announced in the 2016 Ontario budget is a first step in a longer-term strategy to achieve greater equity in compensation within team based primary care. The AFHTO-AOHC-NPAO proposal remains our goal; on behalf of our members, AFHTO will continue to press for the full funding needed to make working in primary care attractive to recruit and retain competent staff in this sector. As for implementation of government’s 2016-17 commitment, approval letters for each FHT, NPLC, AHAC (and through the LHINs for CHCs) are in the final stages of ministry sign-off. We don’t know how long this will take, but hopefully will be “soon”. The funding will be retroactive to April 1, 2016.  Once funding letters are available and Ministry approvals are in place regarding the funding allocation, AFHTO (with MOHLTC participation) will hold technical briefings with EDs & Board Chairs.

    Learning from your peers: additional case studies

    AFHO has developed a series of case studies for our members to share the experience of colleagues on topics identified as being important to you:

  • QIP Analyses: Insights into Quality Improvement

    Each year, Health Quality Ontario (HQO) produces Insights into Quality Improvement, this report highlights exceptional change ideas, emerging trends, and lessons learned from the previous year’s QIPs that can help organizations as they develop their yearly QI initiatives. The summary reports on Primary Care QIPs are available here:

    Additional resources for developing QIPs are posted on the Primary Care Quality Improvement Plans Webpage. Quality Improvement Plans are due to HQO on April 1st each year. If you or your team have any questions about the QIPs or about Health Quality Ontario’s quality improvement resources, please contact QIP@HQOntario.ca.