1. Electronic medical record in private practice
A Method of Collecting and Reorting Outcomes Data .

2. Kai = Change Zen = For The Better
KaiZen®RD EMR
Kai = Change Zen = For The Better
KK Patalano, MBA, RD, LDN, CDE, NHA, Private Practice Dietitian KaiZen® Healthcare Solutions, Boylston, MA. AJ Martin, RD, LDN Private Practice Dietitian
West Acton Villageworks, Acton, MA.
30 plus years as RD
Nutrition Support at UMMC
WPI Management of Technology, 7 years of Systems and Process Engineering
2003 – Software Company KaiZen Healthcare for MA nursing homes Medicaid Billing
2004 Private practice
July 2010 Alexander Martin, who is also my son is a nutrition student at FSU who worked with me as an interm. I was looking to create a way for him to have easy entry into private practice while maintaining the quality of my many years of experience while eliminating paper files, and easy billing.
Used KaiZenRD for 1 year, then showed to RD’s – built by village
Cloud based Jan 2012, Released March 1, The 100th RD signed on on March 1, 2014!
2012 RD’s not reimbursed for weight loss counseling for Medicare – no outcomes data.
KaiZenRD Tool to collect outcomes data

3. KaiZenRD
Kai = Change
Zen = For The Better
Changes in lifestyle factors can prevent 93% of diabetes 81% of heart disease 50% of strokes 36% of all cancers
How many people suffer from Diabetes, High cholesterol, Obesity, Hypertension?
They are predicting that 80% of the US population will be overweight by 2020.
We are all familiar with these lifestyle related diseases...how are we going to attack them? Changes in lifestyle factors can prevent: 93% of diabetes 81% of heart disease 50% of strokes 36% of all cancers
Nutrition counseling has a huge impact in changing lifestyle factors...but there is something holding it back, we have 75,000 dietitians and they do not have a reliable way of documenting outcomes. Prevention of lifestyle related diseases is possible if we give dietitians a tool that can improve the nutrition care process while collecting data to strengthen the foundation of nutrition intervention.

4. KaiZenRD
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Drug use instead of prevention? 60% of Americans are using prescription drugs. 8 of 10 commonly used drugs are used to treat cardiometabolic syndrome, which could be prevented by a healthier lifestyle.
JAMA reported Significant Increases in cholesterol lowering drugs, blood pressure medications and anti-depressants.
Obesity is major factor driving the rise in prescription drug use.
8 of 10 most commonly used drugs are used to treat components of cardiometabolic syndrome.
Many of the drugs are prescribed for conditions that could be prevented by a healthier lifestyle.

5. KaiZenRD
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“Consider the irony. Here in the U.S. we aggressively peddle foods that propogate illness, and drugs to treat the illness that ensues. Big food and Big Pharma are the winners – we and our families, the losers.” – David Katz, MD

6. KaiZenRD
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7. KaiZenRD
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8. records problem: IIlegible, Incomplete and Inefficient Paper Records Paper Records Stored in Non-HIPAA Compliant Manner….
KaiZenRD
Kai = Change
Zen = For The Better
What you are looking at here is a piece of very sad news. Typical state of the art documentation, and it may be the single greatest reason why we are not having the impact on lifestyle related diseases.
Most dietitians are currently using paper medical records which are illegible, incomplete and inefficient. They are often stored in non-HIPAA compliant bins.
Unable to collect outcomes data with paper records, free doctors medical records, or foreign owned software programs.

9. documentation pROBLEM: Patients and Physician Receive Handwritten Notes or Notes are Typed up after Patient Visits
Kai = Change
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Here we have the state of the art documentation…..
Even today, despite the advances of technology most dietitians are still using paper medical records. I was one of those dietitians up until 5 years ago when I had been in practice for 5 years and had to purchase attractive wood file cabinets to lock up all my illegible paper medical records in my home office. This was the deal breaker. I could not get any more files in and I could not take anything out. I had started a software company in 2004, at the same time that I had started my private practice, so I developed an EMR for myself. I used the software for one year, then started responding to dietitians who were posting requests for EMR’s on LinkedIn and Dietitian practice group ListServes. We continued development of the EMR based on dietitian’s requests. The EMR was released on March 1, 2012 and more than 150 dietitians have signed on to date.

10. billing pROBLEM: Costly, Error Ridden and Time Inefficient Billling Process
KaiZenRD
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And the Billing ….
Dietitians are often filling out the 1500 billing form by hand and snail mailing it to insurance companies or are sending the information to a biller who charges 10 – 15% of their revenue to send it to a clearinghouse.

11. OBESITY pROBLEM: KaiZenRD Kai = Change Zen = For The Better
Dietitians don’t have the tools to document the beneficial impacts of nutrition counseling. If we have the evidence that it works, we can have a far greater impact. This is a problem that I have been working on for the past 5 years. I created KaiZen®RD EMR to expand the range of dietitians in private practice by creating a specialized tool they can use to gain accessibility and acceptance. The big impediment is that dietitians are still using paper charts, nutrition counseling can be having a far greater impact if we have better tools to document outcomes.

12. KaiZenRD Kai = Change Zen = For The Better
This is one of my many patients who has lost over 100 pounds after being diagnosed with diabetes. He is eating healthy and exercising regularly and is not on any medications. On April 1 he signed up for his first 5 mile road race in July and is currently in training.
I am sure that you all have such success stories but are unable to document them if you are still using paper medical records.

13. KaiZenRD Kai = Change Zen = For The Better
This is one of my many patients who has lost over 100 pounds after being diagnosed with diabetes. He is eating healthy and exercising regularly and is not on any medications. On April 1 he signed up for his first 5 mile road race in July and is currently in training.
I am sure that you all have such success stories but are unable to document them if you are still using paper medical records.

14. Lab Changes without Medications!
Here are the outcomes results from another patient of mine that has also lost over 100 pounds. She came to see me because she was diagnosed with diabetes but did not want any medications. You can see here that her A1C dropped from 7.4 to 5.1, FBS from 152 to 93 and her LDL is down to 98. Also make note of the corresponding increase in Vitamin D and HDL!

15. learning objectives: TO DEFINE THE METHOD OF USE AND BENEFITS OF AN ELECTRONIC MEDICAL RECORD (EMR) TO: Collect Data Measure Outcomes Document progress REPORT REAL TIME RESULTS IN: Weight Change Laboratory Value Improvments MONITOR: Activity Duration/Frequency Restaurant Frequency and Much More….

16. purpose of study: Academy Statement: “Outcomes data is needed to strengthen the foundation of clinical evidence used by Center for Medicaid and Medicare Services (CMS) and insurers in making coverage decisions.”
In 2012 it was decided by Medicare that RD’s would not be reimbursed for weight loss counseling, because there was no outcomes data. So I decided to make KaiZenRD a tool to collect de-identified outcomes data from all the dietitians using the system, which is what I will be presenting to you today.
In order for dietitians to be reimbursed we need to use a database in our practices in order to collect, report and publish outcomes data. There are many states in the US where nutrition counseling is not covered by insurance and prevention is much less expensive than treatment…
According to a nationwide study conducted in 2012, the cost of diagnosed diabetes is approximately $176 billion each year in medical expenses alone.
Economic costs of diabetes in the U.S. in Diabetes Care Apr;36(4):

17. Kai = Change Zen = For The Better
KaiZen®RD EMR
Kai = Change Zen = For The Better
HYPOTHESIS:
NUTRITION COUNSELING BY REGISTERED DIETITIANS
IS RELATED TO WEIGHT LOSS AND CARDIOVASCULAR
RISK FACTOR REDUCTION.
I would like to Thank The Maine Academy of Nutrition and Dietetics for hosting us And thanks to everyone who hung in there for the final session.
I am excited to talk to you all about the data that I analyzed from this program. Karen is handing off all the number talk to me, but I find these numbers to be really exciting.
Karen’s intention when developing the program was to reduce the barriers for dietitians starting and working in private practice. But now we have collected, unintentionally all this great data. So our research hypothesis was actually formed after the fact of collecting the data, which is a pretty untraditional model for a research study.
State hypothesis:::::::
Not a very revolutionary idea among dietitians, but there is a surprisingly limited amount of solid research on the issue. Most studies include less than 100 participants where by pooling all of the clients in the EMR we were able to collect information on almost 7,000 individual patients.

18. Bradley DW. The Incremental Value of Medical Nutrition Therapy in Weight Management. Managed Care Jan;22(1): First Published Study that Evaluates a Policy Decision by an Insurance Company to provide coverage for MNT: Retrospective Self Reported Both control and experimental groups experienced statstically significant: Weight Loss Decreased BMI increase in Exercise…
The following are some studies which had a similar hypothesis. Bradley, conducted a study in 2013 on he effectiveness of Medical Nutrition Therapy. The methods for this study were self reported and retrospective. Essentially a clinician called the study participant after a session with a dietitian and asked if they had lost weight. They thought so. The accuracy to this method of sample taking is questionable. Actually my favorite part about this study was that the control group, the group who didn’t see a dietitian, they were called and asked it they had suddenly been inspired to exercise and lose weight to which they responded that - Yes, they have been exercising and yes they have lost some weight recently. So the difference between these groups was insignificant. But the reality of weight loss in the experimental group, was enough to justify Medical Nutrition therapy being cost effective. This is because comparatively nutrition intervention is much cheaper than medical intervention including drug administration or renal dialyses.

19. Johnson,EQ, Valera,S. Medical Nutrition Therapy in Non-Insulin-Dependent Diabetes Mellitus Improves Clinical Outcome. J AM Diet Assoc June:95(6) Retrospective Ambulatory Care QA Audit Focused on Clinical Outcomes of NIDDM after MNT N = 19 patients BS decreased by 50% No statistical analysis Unable to obtain info on A1C, Chol TG as sample size too small
This study by Johnson looked at MNT improving blood sugar. However with the sample size being only 19 patients, no significant results could be produced.

20. Delahanty, LM. , Sonnenberg, LM. , Hayden,D. , Nathan, DM
Delahanty, LM., Sonnenberg, LM., Hayden,D., Nathan, DM. Clinical and Cost Outcomes of Medical Nutrition Therapy for Hypercholesterolemia: A Controlled Trial. J Am Diet Assoc Sept: 101(9) 1021 – Cholesterol Lowering MNT without Hypolypemic drugs: 6% Decrease in Chol (69 mg/dl) Activity increased 29 minutes per week N = 90 (60 men, 30 women)
Delahanty, observed significant decreases of LDL cholesterol in patients who received dietetic counseling without the use of cholesterol lowering drugs.

21. METHODS : kpatalano@kaizenrd.com www.kaizenrd.com
The clinical outcomes of Medical Nutrition Therapy by Registered Dietitians in private practice in more than 30 states and Canada was collected, DE-identified and analyzed for weight loss, blood sugar, serum lipid levels, and change in activity levels and restaurant frequency..

22. Patient Information: kpatalano@kaizenrd.com www.kaizenrd.com
the RD enters information into the database at each visit that includes but is not limited to weight, labs, medications, diagnosis, activity frequency and duration, restaurant and take-out frequency.  

23. Weights, laboratory Values, Diagnosis and Meds
Patient Visits:
Weights, laboratory Values, Diagnosis and Meds
De-identified data was analyzed for patients receiving at least two sessions of Medical Nutrition Therapy with a registered dietitian in private practice.
Diagnosis was determined using ICD-9 codes, weight was taken at each visit, laboratory values were entered when available and activity frequency and duration was self-reported by the patient. On December 31, 2014 de-identified data was downloaded, and analyzed using Microsoft Excel, KNIME and R-Studio.

24. Activity and Restaurants:
Activity duration and frequency, Who is cooking, Alcohol consumption, Restaurant and take out Frequency monitored at each visit

25. Diagnosis: ICD-9 Codes kpatalano@kaizenrd.com www.kaizenrd.com
ICD9 codes were used to sort by Diagnosis. We looked at weight change for total then by diagnosis of Diabetes, Obesity, Hypercholesterolemia, Hypertension and Overweight. We Compared original weight to final weight entered.

26. Laboratory Values: KaiZenRD Kai = Change Zen = For The Better
Looked at change in lab values from at least two results entered on different dates. Values were compared to original value for patient so each patient needed to have 2 data points in system.

27. KaiZenRD
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OUTCOMES RESULTS: KaiZenRD Dietitians saw: 6,935 patients in 17,837 visits After an average of 2 visits : 3.2 pounds of weight lost 11 point drop in Cholesterol mg/dl decrease in Fasting Blood Sugar 0.5 point decrease in Hemoglobin A1C
Data
Analysis
Outcomes Results from the 2012 – 2014 Data Mining and analysis are as follows.
Dietitians saw 6,935 patients in 17,837 visits and after an average of only 2 visits their patients lost 3.2 pounds of weight, experienced an 11 point drop in cholesterol, 15.9 mg/dl decrease in Fasting Blood Sugar and a 0.5 point decrease in Hemoglobin A1C.
I like to break up the data I’m about to cover into two parts. One primarily focusing on the blood values of: cholesterol, hemoglobin A1C, fasting blood sugar the other on the Weight Loss.

28. FASTING BLOOD SUGAR DECREASE
Age = 58.5, SD =13.4 n = 120: Male = 37, Female = 65 Visit Duration average: weeks mean = * mg/dl, SD = (t-test: p < 0.01)* 95% Confidence Interval
Age range
2x females than males. 5 months
-15.9 decrease in FBS
At the 95% sig level the data provide sufficient evidence to conclude that the mean FBS differs significantly from the mean FBS prior to nutrition counseling.

29. Hb A1C DECREASE
Age = 57.8, SD = 12.7 n = 135: Male = 52, Female = 55 Visit Duration average: weeks mean = * mg/dl, SD = 1.40 (t-test: p < )* 95% Confidence Interval
Age range , equal number Men and women!
4.5 months
-0.5 decrease in A1C

30. cholesterol DECREASE
Age = 54.2, SD = 13.9 n = 108: Male = 38, Female = 51 Visit Duration average: weeks mean = * mg/dl, SD = (t-test: p = )* 95% Confidence Interval
Age range = 40 – 68
More women than men
4 months duration
-11 point drop in chol
At the 95% sig level the data provide sufficient evidence to conclude that the mean Cholesterol differs significantly from the mean Cholesterol prior to nutrition counseling. For every 1% reduction in total cholesterol levels is associated with a 2% to 3% reduction in coronary heart disease. This group experienced at least a 25% reduction in total cholesterol which would translate to a 50 – 75% reduction in coronary heart disease.

31. LDL DECREASE
Age = 54.2 , SD = 13.9 n = 97: Male = 32, Female = 47 Visit Duration average: weeks mean = * mg/dl, SD = (t-test: p < 0.01)* 95% Confidence Interval
Age range = 40 – 68
More women than men
4 months duration
-8 point decrease in LDL

32. TRIGLYCERIDES DECREASE
Age = 53.7 , SD = 13.2 n = 93: Male = 34, Female = 44 Visit Duration average: weeks mean = * mg/dl, SD = 67.5 (t-test: p = 0.01)* 95% Confidence Interval
Age range 40 – 68
Slightly more women than men
4 months
-40 point drop in TG!
In this review we did not control for medications, That is something we will look into in the future of how we can monitor more closely.

33. Vitamin D
Age = 51.4 , SD = 15.2 n = 36: Male = 9, Female = 21 Visit Duration average: weeks mean = *, SD = (t-test: p = 0.01)* 95% Confidence Interval
Age range = 36 – 66
Number of participants is 36
4 1/2 months
+ 5.5 increase in Vit D Vitamin D is an interesting value because it could show how Dietitian’s are able to influence clients into using supplements that will benefit their health

34. Weight loss: all patients
Age = 45.9, SD = 16.8 n = 2464: Male = 578, Female = 1491 Visit Duration average: weeks mean = pounds* , SD = (t-test: p < )* 95% Confidence Interval
individuals 2464 were included
More than twice as many women
3.5 months
Loss of 3 pounds weight loss I think is the most exciting data to collect. From what we know about Metabolic Syndrome, is that Obesity is a key feature of the syndrome, so even a small amount of weight loss represents a general reversal of the progression of the syndrome. And overall drug intervention such as metphormine or insulin does not generally result in weight loss.

35. Weight loss: diabetes
Age = 58.9, SD = 12.6 n = 453: Male = 154, Female = 243 Visit Duration average: weeks mean = pounds* , SD = (t-test: p < )* 95% Confidence Interval
Age range
34% men, 54% women
4 months
-3 pounds
? Medication effect, Did medication decrease lifestyle change for diet and exercise.
Future: increased sample size with and without meds

36. weight loss: hyperlipidemia
Age = 50.8, SD = 13.6 n = 108: Male = 25, Female = 71 Visit Duration average: weeks mean loss = pounds* , SD = 5.31 (t-test: p < )* 95% Confidence Interval
Age range
3 times as many women
4.5 months
2.7 pounds
? Medication effect, did medication decrease lifestyle change.
Future: Increase sample size look at meds vs. no meds

37. weight loss: Obesity
Age = 39.7 , SD = 13.4 n = 580: Male = 140, Female = 419 Visit Duration average: weeks mean = * pounds , SD = (t-test: p < )* 95% Confidence Interval
Young age group 27 – 53yrs,
24% male, 72% female
3 months

38. Body fat percentage
Age = 42.1 , SD = 15.9 n = 222: Male = 62, Female = 148 Visit Duration average = weeks mean = - 1% *, SD = 3% (t-test: p < )* 95% Confidence Interval
Age range = 26 – 58
More than 2x women
4.5 months
Loss of 1% body fat

39. Overweight – weight loss
Age = 40.9, SD = 14.7 n = 193: Male = 48, Female = 142 Visit Duration average = weeks mean = pounds* , SD = 7.72 (t-test: p < )* 95% Confidence Interval
26 – 56
3 times as many women
3 months
3 pounds

40. Hypertension – weight loss
Age = 48.8 , SD = 12.5 n = 70: Male = 17, Female = 49 Visit Duration average = 8.32 weeks mean = pounds* , SD = (t-test: p = 0.01)* 95% Confidence Interval
37 – 61
24% male 70% women
2 months
- 3.8 pounds

41. Activity duration increase
Age = 42.8 , SD = 15.5 n = 586 : Male = 158, Female = 356 Visit Duration average: weeks mean = +21 Minutes/week* , SD = (t-test: p < 0.001)* 95% Confidence Interval
Range of yrs 28 – 58
2 ½ times as many women as men
4+ months
+ 21 minutes per week
At the 95% sig level the data provide sufficient evidence to conclude that the mean activity duration differs significantly from the mean activity duration prior to nutrition counseling.

42. Kai = Change Zen = For The Better
FUTURE
Analyze for Laboratory Value Changes with and without Medications.
Develop Methods to Provide Analysis for Individual Dietitians or Group Outcomes Quarterly.

43. kpatalano@kaizenrd.com www.kaizenrd.com

44. PQRS: Preventive Care and Screening BMI. 18 Years +
PQRS: Preventive Care and Screening BMI Years + Minimum once per year Normal BMI: 65 Yrs+: BMI = – 64 Yrs: BMI 18.5 – If above or below normal BMI, document and have a follow-up plan. CPT CODES: , 97803
In order to bill using PQRS you need to document the BMI which is automatically calculated when height and weight in entered into the EMR

45. pqrs: Preventive Care and Screening BMI Codes and Description: G8420 – Normal BMI G8417 – Greater than Normal, follow-up documented G Less than Normal, follow-up documented G8938 – Calculated but patient not eligible for f/u G8422 – Not documented G8421 – Not calculated, document* reason why G8419 – BMI < or > norms, no follow up documented* * Documentation on worksheet and in the medical chart

46. PQRS: Documentation of Current Medications in Medical Record
PQRS: Documentation of Current Medications in Medical Record 18 Years + At each visit All current RX, OTC, herbals, vitamin/ mineral dietary supplements. Medication name, dosage, frequency and route of administration Report whether you documented a list of patient’s medications, including all parameters. CPT Codes: , 97803, 97804, G0270
Medications, which I just scan in
I usually just enter what the medication does and whether it is going up or down but for PQRS billing I scan the medications into the system.

47. pqrs: Domentation of Current Medications in Medical Record Codes and Description: G8427 – Documented G8430*– Not documented, *Document reason why G8428* - Current meds not documented, reason not given. * Documentation on worksheet and in the medical chart

48. PQRS: DM Hemoglobin A1C Poor Control. 18 - 75 Years
PQRS: DM Hemoglobin A1C Poor Control Years Minimum once per year Most recent A1C Report: A1C > 9.0%; or 7-9% or < 7% with ICD-9 diabetes codes CPT Codes: , 97803, 97804, G0270, G0271
A1C which we monitor whenever available.

49. pqrs: DM A1C Poor Control Codes and Description: 3046F – A1C > 9
pqrs: DM A1C Poor Control Codes and Description: 3046F – A1C > 9.0% 3045F – A1C = 7.0% - 9.0% 3044F – A1C < 7.0% 3046F-8P – A1C not performed during the performance period of 12 months

50. PQRS: ELDER MALTREATMENT screen and follow-up plan. 65 Years +
PQRS: ELDER MALTREATMENT screen and follow-up plan Years + Once per reporting year Documented elder maltreatment screen and a documented follow-up plan on the date of a positive screen. Report whether or not you screened for elder maltreatment and documented a follow up plan if necessary.

51. PQRS: ELDER MALTREATMENT screen and follow-up plan Codes and Description: G8733 – Positive Screen and f/u documented G8734 – Screen documented, no follow up plan because screen was negative G Screen documented, patient not eligible G8535 – Not screened, patient not eligible G8735 – Screen positive, follow-up plan not documented, reason not given G8536 – No documenteation of maltreatment screen, reason not given

52. PQRS Medicare Billing ELDER MALTREATMENT SCREENS:
Hwalek-Senstock Elder Abuse Screening Test
Vulnerability to Abuse Screening Scale
Elder Abuse Suspicion Index
I complete one of these screens on paper and scan them into the EMR
Hwalek-Senstock Elder Abuse Screening Test Vulnerability to Abuse Screening Scale Elder Abuse Suspicion Index

53. PQRS Medicare Billing kpatalano@kaizenrd.com www.kaizenrd.com
9 Entries on the Billing form completes all 32 required entries….without errors.
Need to enter the date of service
Place of service from dropdown
CPT codes – cheat sheet included
Dx Pointer
Charges of 0.01
Units 15 minutes = 1 unit

54. PQRS Medicare Billing kpatalano@kaizenrd.com www.kaizenrd.com
9 Entries on the Billing form completes all 32 required entries….without errors.

55. kpatalano@kaizenrd.com www.kaizenrd.com