Primary Care Patient Satisfaction Survey 2019

Primary Care Patient Satisfaction Benchmark Report

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A decrease of 6.9% in positive ratings in 2019 indicates a decline in the overall patient satisfaction level.

Key Takeaways

  • 90.4% of patients gave postitive ratings about their visit to primary care physicians in 2019, whereas it was 97.3% in 2018.
  • 4.2% rated their experience neutral, whereas it was 0.3% in 2018.
  • Overall, the Net Promoter Score (a measure of patient’s loyalty) for physicians is 87.6/100 (Total Sample = 84,865), whereas it was 83.8/100 in 2018.
    • 90.4% of the patients are Promoters (patients who are likely to refer a specific practice/doctor to a friend or family member), up by 0.4% when compared to 2018.
    • 6.9% of the patients are Passives (patients who are likely not to take any action in referring a specific practice/doctor), whereas it was 7.4% in 2018.
    • 2.8% of the patients are Detractors (patients who are likely to deter people from choosing a specific practice/doctor), whereas it was 2.6% in 2018.
  • Listens, Professional, Knowledgeable, and Caring were the dominant words used by patients who rated their experience as positive.

Welcome to the GMR Web Team Primary Care Patient Satisfaction Survey (2019)

Since the inception of our first patient satisfaction survey report (January-June 2017), we have seen some changes in the ways patients review their healthcare visit experience, but mostly in how we analyze it. This survey follows on from our first report, comparing the useful insights on reviews and patient satisfaction. The data was taken from our proprietary software RepuGen.

This survey measures the LOYALTY of patients for their primary care physicians and helps physicians understand the needs of their patients for developing effective patient-related programs to address their pain points. This will help in developing a stronger bond between patients and physicians, and the patients will become the advocate of their physicians, resulting in more referrals and fueling growth.

How Do Patients Rate Their Visit to Primary Care Center Office Based on Their RepuScore*?

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*RepuScore is the score given by patient on a scale of 0 to 10 when asked their likelihood of recommending the physician based on their experience of the last visit. 0 means will not recommend, and 10 means will recommend.

Key Findings

  • The Average RepuScore remained the same 9.6 in 2019, 2018, and 2017.

Analysis

  • Given that the primary care centers in this study were using GMR Web Team tools to address patient complaints, it is not surprising that the likelihood of recommending the physicians remains the same (above the already high levels of the benchmark study).
  • This also validates our view that paying more attention to patient experience is the key to getting more recommendations from patients.

All Ratings (Rating Breakdown)

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Key Findings

  • Consistent with the overall data, more patients rated their experience as positive. However, it decreased by 6.9% in 2019 as compared to 2018.
  • Patients rating their experience neutral increased by 3.9%, whereas ones rating as negative increased by 3.1% in 2019 as compared to 2018.

Analysis

  • More positive ratings suggest that the efforts by primary care centers to address their patients’ concerns are helping to improve the patient experience. However, a decrease when compared with the last survey is a matter of concern.
  • Primary care centers need to focus more on the patient experience and pain points to increase patient satisfaction.
  • The increase in negative ratings also suggests that maybe patients are becoming more passionate about their care, so that a neutral rating just doesn’t cut it – they’re either happy or not happy.
  • Primary care centers must compare their individual scores with the overall numbers to identify areas for improving the patient experience when they visit the office.

Net Promoter Score Breakdown

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**The Net Promoter Score is an index ranging from -100 to 100 that measures the willingness of customers to recommend a company's products or services to others. It is used as a proxy for gauging the customer's overall satisfaction with a company's product or service and the customer's loyalty to the brand.

Key Findings

  • Net Promoter Score saw an increase of 3.8% in 2019 when compared to 2018.
  • Percentage of patients who could become promoters decreased by 0.5% in 2019 when compared to 2018.
  • 2.8% of patients were not likely to recommend their primary care center as compared to 2.6% in 2018.

Analysis

  • The increase in Net Promoter Score in 2019 suggests an increase in patients’ loyalty to their primary care center, as well as how increasingly important patient referrals are becoming.
  • Overall, 9.7% of patients are not likely to refer people to their primary care physician.
  • Primary care centers need to look at their individual scores and compare with the average number to identify areas where they are doing better and areas where they need to improve.

Patient Sentiment Analysis *** after their visit:

*** Patients are asked to explain their reason for rating their visit the way that they did. GMR Web Team analyzes sentiments and its intensity based on the comments, using an artificial intelligence tool. This gives a better perspective on satisfaction, as a rating of 10 could still be a so-so experience from a patient.

Patient Sentiment Trends

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Key Findings

  • Positive sentiment saw a slight increase of 0.2% in 2019 as compared to 2018.
  • There was a slight decrease of 0.3% in neutral sentiment in 2019 compared to the last report (2018).
  • Negative sentiment remained the same 10.1% in 2019 and 2018.

Analysis

  • Primary care centers need to identify patients who showed neutral and negative sentiment and address them personally as soon as possible.
  • The reason this is so vastly different from the RepuScore is that this relies on artificial intelligence to scan the REAL comment of the patient, not just their 0-10 rating.
  • Ratings are generally a less accurate way to measure a comment, as the most common ratings are a 10 or 0 – yet most people who rate this high or low are not this happy or dissatisfied.
  • You need to measure the context of their comments, which is what this AI sentiment analysis tool does – at about a 3% margin of error.
  • This also shows the online review scores aren’t always an accurate portrayal of reputation, based on how much the ratings are skewed.
  • Note that a negative sentiment doesn’t equal an unhappy patient. Taking a comment as a whole, an AI sentiment analysis tool could take a positive rating as negative for something as simple as ‘the wait time was too long.’

Word Cloud Analysis****

**** Word cloud analysis uses the frequency of words used by patients and picks up the most used words. Size of the word denotes frequency in the chart.

Positive Ratings -- Top 20

2017

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2018

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2019

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Key Findings

  • Listens, Professional, Caring, Friendly, and Knowledgeable were the most used words among patients who rated their visit between 9 and 10.
  • Helpful, Attentive, Answered, Excellent, and Recommend were some other frequently used words.

Analysis

  • Frequently used words by satisfied patients should resonate a positive sentiment, and thus could be used to build expectations for new patients, knowing fully well that it will resonate and that the practice will be able to fulfill the promise.
  • An example could be making a bold statement like Listens, Caring, Friendly, Professional – these are the most used words that patients use to describe their visit.

Negative Ratings -- Top 20

2017

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2018

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2019

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Key Findings

  • Appointment is the most frequently word used by unhappy patients.
  • Pain, Waiting, Minutes, Questions, and Medication are other negative words used by patients.

Analysis

  • Frequently used words by unhappy patients allow the primary care centers to gauge patients’ reasons for dissatisfaction.
  • However, given the fact that the comments of patients were detached, we can assume that Appointment, Pain and Waiting were among the major concerns. These words are more relevant when linked to the patients (which GMR Web Team account holders can do), and also when analyzing the complete review written by the patients.

About the GMR Web Team Primary Care Patient Satisfaction Survey

  • An online survey was conducted from January 2019 through December 2019 among 84,865 patients, belonging to primary care centers that are using GMR Web Team service. We included the data of 2018 and 2017 to show the actual trends over the years.
  • The patients were asked to select their likelihood of recommending the physician based on their latest experience on a scale of 0 to 10.
  • Patients were asked to explain the reason behind their rating.
  • All the information (rating score and comments) was detached from patient and doctor identification to make the report HIPAA* compliant. GMR Web Team cannot backtrack comments or sentiments to link Net Promoter Score or sentiment to any patient or physicians that were used for this report.

*HIPAA - The Health Insurance Portability and Accountability Act, a US law designed to provide privacy standards to protect patients' medical records and other health information provided to health plans, doctors, hospitals and other health care providers.

  • Patients were then classified into 3 categories – Promoters, Passives, and Detractors.
    • Promoters: Patients giving a rating of either 9 or 10 to their physicians were classified as Promoters. They are loyal enthusiasts who will keep referring the physicians to other patients.
    • Passives: Patients giving a rating of 6 to 8 to their physician were classified as Passive. They are satisfied but NOT enthusiastic patients who are vulnerable to competitive offerings
    • Detractors - Patients giving a rating of 0 to 5 to their physician were classified as Detractors. They are unhappy patients who can damage the reputation of their physician and impede growth through negative word of mouth.
  • All comments were grouped by positive, negative, and neutral ratings.
  • GMR Web Team proprietary software RepuGen was used to gauge patient sentiment by group (positive, negative, neutral) and also to gauge the intensity of the sentiment based on their comments about their experience.
  • RepuGen was used to analyze word density of comments by the group of patients to identify words used by patients to describe their experience.

Why Is the Primary Care Patient Satisfaction Benchmark Report So Important?

Online reviews and recommendations from existing patients are the best source of new patients for primary care physicians.

  • In-depth analyses of patient experience help physicians identify their strengths and weaknesses, giving them the knowledge to make positive organizational changes.
  • Understanding the patient sentiment and its intensity provides insight into the patients’ mindsets after they leave the office. Physicians can use the information to improve satisfaction and brand their practice consistent with the positive sentiments generated by their service.
  • The density of words extracted from patients’ comments of different groups will help communicate the desired branding effort better.

Suggested Next Steps:

Primary care physicians and family medicine practices should gather patient experience information to better understand patient sentiment, and ultimately improve patient care and satisfaction.

Patient satisfaction data can also be used to attract more patients by:

  • Improving online reputation by requesting happy patients to share their information on the internet. Over 30% of prospective patients select their doctor solely based on their online reviews.
  • Developing an automated referral program that requests happy patients to recommend their doctor or family medicine practice to others.

Contact us at 800-523-7187 or fill out our form to learn how you can start building your patient satisfaction data and how to use it to generate more patients.

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