How to work with physicians to improve data quality and funding

How to work with physicians to improve data quality and funding

Physicians learn many things during their years of training. Unfortunately for the people who work in hospital Health Records and Decision Support departments, clinical documentation is generally not one of them.


Since the launch of Health System Funding Reform (HSFR) in 2012, up to 70% of a hospital’s annual funding is based on their performance relative to other hospitals in Ontario. Efficiency is measured in terms of cost per weighted case, with the denominator directly coming from the output of Health Information Management (HIM) professionals coding and abstracting from physician documentation of discharged patients.

In the years since the introduction of HSFR, hospitals across Ontario have realized the critical impact that high quality documentation and coding has on their revenue cycle. Improving the coding component, is relatively straight-forward.  Hospitals have adopted lean process improvements to streamline the Health Records function though tighter business practices. They have hired data quality staff (or, in most cases, repurposed existing coders) to focus on educating their HIM team and conducting audits and data quality checks. Many hospitals have also invested in Data Quality Assist, a software solution to help guide data quality efforts.


Improving the first component of the equation, physician documentation, is much more challenging than the coding element. To start with, CIHI coding standards and both ICD-10 (diagnosis) and CCI (intervention/procedure) codes often do not align with how physicians describe patients, their diagnoses, and the care they provide. This can create a problematic ‘language barrier’ between physicians and coders. A perfect example of this is the Most Responsible Diagnosis (MRDx) concept. CIHI defines MRDx as the one diagnosis most responsible for the longest component of the patient’s stay and/or most resources used. For standard admissions with no comorbidities or complications, this is generally simple for the physician to document and the HIM professional to code. For example, a patient admitted for a urinary tract infection that has no other complications or underlying diagnoses would have a straight-forward discharge summary and the coder can easily determine that the UTI is the MRDx.


However, with Ontario’s aging population and increased prevalence of people living longer with multiple chronic conditions, most patients have more than one diagnosis (or comorbidity) associated with an inpatient admission. It is not uncommon for long-stay patients to have over 10 diagnoses. Another common phenomenon is when the MRDx is different from the admitting diagnosis. In our UTI example above, imagine the patient caught a hospital-acquired infection which significantly extended their stay. If, for example, the physician does not clearly document that it was the C-diff that led to the long stay, the patient may be coded with the MRDx of UTI, carrying with it the subsequent negative Health Based Allocation Model (HBAM) funding implications.

Another consideration is the utilization and cost differences associated with different components of the patient’s stay. In UTI example above, the resources used for the short stint the patient may have had in the ICU (with one-to-one nursing) might be greater than the resources used when the patient was being treated for the UTI in the ward room.

Physicians generally do not think in terms of MRDx. The attending physician is typically first interested in the admitting diagnosis, which often made by the physician in the ED. The Most Responsible Physician (MRP) at discharge is then concerned with providing a discharge diagnosis back to the patient’s primary care physician to support ongoing / follow-up care post-discharge. Often the MRDx is different than these two diagnoses. To be sure, in my 7 years of working with physicians on data quality projects I have never met a physician who initially understood what CIHI is looking for with MRDx.


In most teaching hospitals it is the residents and fellows that document care, with staff physicians having varying levels of engagement in the process. Health Records departments in teaching hospitals need to understand their current state in terms of who does what (trainees vs. staff physicians) and tailor their education and engagement strategies accordingly.


Hospitals have designed initiatives to educate physicians on the importance of high-quality documentation. When considering this approach, Health Records teams should ask themselves if “the juice is worth the squeeze?” For example, in-person education for specific physician teams (where they review their own cases and discuss the most common documentation issues for their subspecialty) is the most comprehensive approach. It is also the most time-consuming and difficult to spread and sustain.

One best practice is to focus any in-person education on physician teams / services where you have evidence of the most room for improvement in terms of documentation and data quality. Health Records departments should apply an effort versus impact lens before embarking on an in-person physician education strategy.


In the United States, where CMS has had performance and quality-based funding for decades, clinical documentation improvement is a major focus for hospitals. Billing offices review physician documentation in real-time and often alert physicians when additional clarity or specification is required prior to the patient being discharged. The myriad of quality-based payments and incentive programs also necessitate more comprehensive documentation, with a clear business case for the hospital investing in data quality initiatives.

While the business case for concurrent coding does not exist in Ontario yet, we should look south to understand the importance of high quality data. Everyone expects Ontario to move further towards performance- and outcome-based funding (see the recent announcement of the new LQ2F pilot for 18/19) and as this transition continues to occur, data will matter even more. I believe the writing is on the wall: true value-based care is on the horizon, bringing with it more bundled payments, a population health focus, and potentially shared risk models with more hospital accountability. The level of disruption that HBAM had on hospitals would pale in comparison to the transformative impact that these sorts of contracts could have. Apart from preparing for the ongoing evolution in the funding environment, there are positive externalities associated with making these sorts of changes now: focusing on understanding your cost structures and cost drivers at the population level and linking that effectively to patient utilization data and quality metrics lays the foundation for broader improvement work.


Understanding the current state of your physician documentation, from a wide-ranging quality perspective (accuracy, comprehensiveness, timeliness, etc.) is a critical first step. 3terra has helped hospitals determine how much room for improvement they have using DQA and through detailed benchmarking with peer organizations for specific populations. Hospitals should then prioritize their improvement initiatives in order to have the most impact. Success in clinical documentation improvement requires a focus on gradual yet continuous improvement, leveraging an approach that targets specific physicians and patient populations over time.

Data should drive decision-making in healthcare for both clinicians and administrators. High quality clinical coded data is necessary to understand and prioritize quality improvement efforts, to drive efficiency initiatives, and to ensure your hospital is being appropriately compensated for the level of care provided.

About Tyler Chalk: Over the last 10 years, Tyler has been leading transformation initiatives at Ontario’s Ministry of Health and Long-Term Care and various hospitals across the province. His focuses have been on strategies and projects that increase operational efficiency and enhance quality outcomes.