Determining the Response Time of Secondary Care Physicians, When Sending Reports

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1 Determining the Response Time of Secondary Care Physicians, When Sending Reports A qualitative and quantitative analysis of the response time of secondary care physicians, when sending back referral reports to the primary care staff at the Orange Blossom Family Health Center. By Christopher Hillhouse MD Candidate 2016, University of South Florida, Morsani College of Medicine GE-National Medical Fellowship Primary Care Leadership Program, July, 2012 A Note on the Study Design: Initially when I arrived at the Orange Blossom Family Health Center I was interested in researching the Hemoglobin A1C levels of diabetic patients and determining whether poor performance was a result of patient noncompliance to treatment or simply due to the progression of the disease. All our uninsured patients must receive their insulin from the onsite pharmacy via the Patient Assistance Program (PAP). I intended to track whether patients were picking up their insulin on a regular basis to determine compliance. I learned however, that to qualify for PAP you have to be a patient that has a history of compliance. Any patient that misses their lab and primary care appointments are not permitted in the Prescription Assistance Program, which is comprised of companies who give their prescriptions for free or at a heavily discounted rate. I turned my attention to system integration after discussing the many concerns the health care providers at the clinic had when communicating with secondary care providers. Background: Over the last few decades there has been a substantial increase of specialty/secondary care physicians. This development has led to a more in depth knowledge in areas that we were 1

2 previously less equipped. However, this change in physician distribution has led to another issue that can no longer be ignored by the health care industry, government and society. The increase in the number of secondary care physicians has led to a decrease in primary care physicians. During World War II, about half of United States physicians were in primary care. Now the base of the health care system has dwindled to less than 30% (Geyman, 2011). This trend portrays a dim outlook on supply and demand in the realm of primary care. Aside from the concerns in the areas of prevention and the increased manifestation of metabolic syndrome (high blood pressure, diabetes, obesity, dyslipidemia and high cholesterol), this issue has also effected the area of system integration. The rift between primary and secondary care has expanded to the area of communication, particularly in the area of referrals. According to the OnMedica report that interviewed 686 physicians, and found that 56% of physician believe that the communication between general practitioners and consultants has become worse (OnMedica, 2011). 2

3 Table 2. Over the past 10 years, do you think that communication between GPs and consultants has: The two main reasons given were that efficient communication is hindered by too much bureaucracy and general practioners and consultants are not engaging with each other in a clinical environment. Both of which are examples of communication barriers. 96% of physicians agreed that at some level, the patient care is suffering due to communication difficulty between primary and secondary care physicians (OnMedica, 2011). This is most present in regards to referrals. Table 5. From your experience, is patient care suffering due to communication difficulties between primary and secondary care? Another study done by Schoen, C. & Osborn, R. involved a survey given to primary care physicians over 10 countries. In each country, only a minority of primary care doctors reported always receiving timely information from specialists to whom they have referred patients (Schoen, C. & Osborn, R., 2013). According to the responses of physicians regarding communication with specialists, failures to coordinate care was a common theme in all of the 3

4 countries surveyed. More than half of the doctors in France and Switzerland said that they always received a report with relevant information after one of their patients was seen by a specialist, compared to fewer than 20 percent of doctors in Germany, the Netherlands, and the United States (Schoen, C. & Osborn, R., 2013). My project is designed to determine the response time of secondary physicians, when sending reports back to the primary care staff at the Orange Blossom Family Health Center. I chose this project topic because one of the concerns many physicians in the center have, is the constant lack of information they receive from consulting secondary physicians. In many circumstances, patients will come to the center for a follow up to their secondary care visit, and the center will have no information regarding the visit. This creates a situation where the primary care physician doesn t have all the necessary information to their disposal, and may be forced to schedule another appointment. Using the electronic medical records system I will determine the amount of referrals and if a follow up report was sent back to the clinic and how long did it take. Also I ll compare the speed of referral times between patients with insurance and those that are uninsured. Uninsured referrals are handled through Orange County. Methods: 4

5 A report containing the total amount of referrals was acquired via the Electronic Health Records system (EHR). The report was comprised of the patient s name, type of secondary care requested, referral date and the primary care provider. It was determined that a 9 month sample would be collected from August 2012 April The sample stopped at April due to the Orange Blossom Family Health Center 60 day policy on referrals. This would prevent the impingement of referrals whose due dates have not been passed yet. Due to time constraints however, the data was limited to the end of March Along with the printed report, two computers were used. One personal computer contained the spreadsheet used to collect the coded data (data sheet contained no patient identifiers), while the HCCH distributed computer contained the EHR. Both the referral paper and HCCH computer remained at the center to oblige by the HIPPA guidelines. After being granted access to the Citrix login system, the EHR was used to search the patients on the referral list one by one. Each patient was searched using their name and referral date found on the referral list. After the patients has been identified in the EHR, the patients demographic data was recorded (age, gender, race, insurance/uninsured, secondary care needed, provider). The patient s actual referral can be found under the order tab. It will be titled under the type of secondary care being requested. For example if the service requested was for acne it would be listed under dermatology. Once you click on the referral you will see information for when the referral was requested, which is generally the same date as the Primary Care appointment. To make sure they are the same date, go to the appointments tab and verify. Under the electronic referral section you ll also be able to verify that the provider on the paper referral report is the same as the one on the EHR. Also you can record the date that the referral was officially ordered. To determine Referral Process Important Dates (Secondary Care Physician Appointment, Appointment Completed, Primary Care Receives Report), one would have to go to the imaging tab and search for the information. This is the most time consuming portion of the data collection, along with the most unreliable set of data. There doesn t seem to be any particular system for recording incoming 5

6 reports, so the labeling of the reports varies from patient to patient. All patients who have no information available were given n/a with no notes. If a document was found to contain the reason why a patient did not attend a secondary care visit, it was written down under the notes section of the spreadsheet. All patients/referrals were recorded in the spreadsheet, however patients who were referred for psychiatric reasons were not included in the data. This is due to the fact that psychiatric referrals and reports are governed by a different set of rules. HOPE Team (Homeless Outreach Partnership Effort) referrals were also left blank. The HOPE team s main goal is to establish a link between the center and the Orlando homeless population. Below is an example of the spreadsheet that was used. Demographic Data Referral Process - Important Dates Referral Time Frame Notes Age Gender Race Insured or Uninsure d 56 M U U Secondary Care Need Provider Initial Primary Care Appointmen t Completed Referral Order Date Secondary Care Physician Appointme nt Appointment Completed (Y/N) Primary Care Receives Report Total Referral Process Gastoenter ologist Lindsey 8/2/2012 9/10/ /8/2012 N/A N/A Not Completed 41 F B I Surgeon Lindsey 8/8/2012 8/9/2012 N/A N/A N/A Not Completed DNKA (Secondary) DNQ for Orange County 64 M B U Cardiologist Torrellas 8/15/ /22/ /26/2012 N/A N/A Not Completed Results: The data of 373 patients were collected during the study. Of the 373 patients, 226 were uninsured patients, while 147 had insurance. The mean age of the patient population was 51.3 with a standard deviation of The charts below show the patient breakdown in the demographics of gender and race. Gender Race Male Asian Black Hispanic Female Indian Other White 6

7 Gender Race 61.93% 38.07% Male Female 2% 19% 1% 20% 1% 56% Asian Black Hispanic Indian Other White The data showed that of the 373 patients, 271 had uncompleted referrals (73%), 76 had completed referrals (20%), and 26 were patients (7%) referred for psychiatric reasons or to the HOPE Team (Homeless Outreach Partnership Effort). A patients referral was labeled uncompleted if the primary care physician had not received any documentation from the secondary care physician. If there were no documentation found in the EHR database the patients referral would be considered incomplete. However the reasons on behalf of the incompletion were searched for in the EHR database under each individual patient. It was determined that 6.3% of the patients that were listed as incomplete, did not keep their secondary care appointment (DNKA). 10.3% of the patients that were listed as uncompleted did not qualify for the service that they were requesting. This could range from a number of reasons; citizenship status, Orange County residency (uninsured population), and the coverage of a particular service, etc. Another 8.9% of patients listed as uncompleted had not returned to the clinic since they re initial primary care visit, and.4% of the patients that were listed as uncompleted refused the secondary care advised by the physician. 74.2% of patients listed as uncompleted did not have a reason or documentation listed in the database. Of the 76 patients that were found to have completed referrals, 58 were returned within the Centers 60 day policy (76%). 18 were returned after the 60 day period (24%). The average amount of time for the completed referrals was 46 days. 7

8 Due to the varying restrictions and guidelines, referrals for psychiatric issues were counted but not analyzed for completion. Referrals to the HOPE team were also not analyzed for completion. This left out 26 patients of the 373 (6%). Of the 147 patients that were listed as insured 79.6% had uncompleted referrals, 16.3% had completed referrals, and 10.2% were referrals for either psychiatric or HOPE Team needs. Of the 24 insured patients that were listed as completed, 22 were completed within the 60 day period (91.7%), whereas only 2 missed the 60 day deadline (8.3%). The average time it took to complete a referral was 38 days. Of the 52 uninsured patients that were listed as completed, 36 were completed within the 60 day period (69.2%), while 16 missed the 60 day deadline (30.8%). The average time it took to complete a referral was 49 days. Data was also collected based on race, gender, specialty, age and primary care provider. The data was collected for the center to determine what was of interest to them. Discussion: The findings of the data collection showed that there is a systematic problem with the referral system. Due to a multifactorial problem, there isn t one area that can be pointed to that would account for the 54% of patients whose referrals were uncompleted with no known reason. The lack of a comprehensive referral list prior to this study hinders the centers ability to track and ensure the status of patient referrals. Currently to determine the status of a referral you would have to go into each individual patient s health records and search through the documents. This only allows for referral verification if the patient s situation is presented to the physician. With a comprehensive referral list in place, it would allow any health staff to go back and verify the status of a patient s referral. Even for patients who do not qualify for service or do not show up to their appointments, it is essential that the center have that information documented. Along 8

9 with the lack of a tracking system, the inputting of referrals is not standardized in the health care center, particularly when it comes to labeling incoming documents in relation to referrals. Appropriate Standardization It was found on a number of occasions that the referral report was in a file that wasn t clearly labeled. This may be a contributor to possible data collection errors. Also the current process doesn t provide an easy way to determine order dates, or even the date that the health center received the report from the secondary care physician. The data showed an increased percentage of the uninsured population having their referrals completed (23% vs. 16.3%). However due to the uncertainty of the status of the uncompleted referrals, this data collection should not be used as an indictment on the process that insured patients go through vs. uninsured. Rather the data shows a combination between the lack of standardization, referral tracking, and communication between all parties in the referral process. No firm conclusion can also be made based on a patient s gender, age or race, the specialty care the patient has been referred to, or the primary care provider. Of the specialty care that patients were referred to, gastroenterology had the most referrals (56). The data collection also revealed that the main age group for referrals, by far is within the year old group, making up nearly 64% of the total referrals. In conclusion, it appears that no definitive assessment can be made about the referral process until the following issues are addressed; A more comprehensive approach to referral tracking Standardized labeling of incoming documentation. At this time due to the above variables, the data is not sufficient to make an accurate assessment on the referral process between insured vs. uninsured patients, and whether or not secondary care physician are returning referrals in a timely manner. Hopefully the datasheet collected can be used as a good starting point to create a comprehensive referral list. 9

10 References 1. Beaulieu, M. (2013) Breaking down barriers for our patients with chronic diseases. Canadian Family Physician, 59, The College of Family Physicians of Canada (2009) Guide to enhancing referrals and consultations between physicians, 1, Farup, P. (2011) What causes treatment failure the patient, primary care, secondary care or inadequate interaction in the health services. BMC Health Services Research, 11(111), Geyman, J. (2011) The Decline of primary care: The silent crisis undermining US health care. Physicians for a National Health Program. Retrieved from 5. Kripalani, S. (2007) Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. American Medical Association, 297(8), Lewis, M. (2012) Enhancing communication between GPs and hospital consultants. Health Service Journal, 1. Retrieved from 7. OnMedica (2011) Primary and secondary relationships. On Medica, 1, Schoen, C. & Osborn, R. (2012) A survey of primary care doctors in ten countries shows progress in use of health information technology, less in other areas. Health Affairs, 1, Schoen, C. & Osborn, R. (2012) The commonwealth fund 2012 international health policy survey of primary care physicians. The Commonwealth Fund, 31(12), Data: Data Statistics n 373 Mean Age(years) Standard Deviation of Age Min Age(years) 19 Max Age(years) 88 10

11 Referrals by Race Total Number of Patients Not Completed Completed Mental & HOPE Team Asian 5 3 (60%) 2 (40%) 0 Black (75%) 43 (21%) 9 (4%) Hispanic (75%) 11 (14%) 9 (11%) Indian 2 1 (50%) 1 (50%) 0 Other 9 8 (88%) 1 (12%) 0 White (63%) 18 (25%) 8 (11%) Number of Referrals Completed Referral by Race Number of Referrals Average Number of Days it took to Complete a Referral Asian Black Hispanic Indian Other White Referrals by Gender Total Number of Patients Not Completed Completed Mental & HOPE Team Male Female Completed Referrals by Gender Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral Male Female Secondary Care Breakdown of All Referrals Total Number of Patients Not Completed Completed Behavioral Health Cardiologist Colon & Rectal Surgeon Dental Dermatologist

12 Endocrinologist ENT Gastroenterologist Geriatrics Gynecologist Hand Surgeon Health Department Hematologist HOPE Team Infectious Disease Lakeside Behavioral Health Mammogram Nephrologist Neurologist Neurosurgery Obstetrician Occupational Therapy Ophthalmologist Optometry Orthopedic Surgeon Orthopedist Pain Management Physical Therapy Plastic Surgeon Podiatrist Psychiatrist Pulmonologist Rheumatologist Shepherd's Hope Surgeon Urologist Vascular Surgeon Vision Center Secondary Care Breakdown of Completed Referrals Number of Referrals Within 60 Days Number of Referrals After 60 Days Average Number of Days it took to Complete a Referral Behavioral Health Cardiologist Colon & Rectal Surgeon Dental Dermatologist Endocrinologist

13 ENT Gastroenterologist Geriatrics Gynecologist Hand Surgeon Health Department Hematologist HOPE Team Infectious Disease Lakeside Behavioral Health Mammogram Nephrologist Neurologist Neurosurgery Obstetrician Occupational Therapy Ophthalmologist Optometry Orthopedic Surgeon Orthopedist Pain Management Physical Therapy Plastic Surgeon Podiatrist Psychiatrist Pulmonologist Rheumatologist Shepherd's Hope Surgeon Urologist Vascular Surgeon Vision Center Referrals by Age Total Number of Patients Not Completed Completed Mental & HOPE Team (50%) 0 1 (50%) (72%) 13 (20%) 5 (8%) (72%) 45 (19%) 20 (9%) 61 & up (73%) 18 (17%) 0 13

14 Completed Referrals by Age Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral (77%) 3 (23%) (73%) 12 (27%) & up 15 (83%) 3 (17%) 42 Referrals by Provider Total Number of Patients Not Completed Completed Mental & HOPE Team Cadet Lindsey Luciano Torner Torrellas Completed Referrals by Provider Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral Cadet Lindsey Luciano Torner Torrellas Gender Male Female 14

15 Race Asian Black Hispanic Indian Other White Insured vs. Uninsured Paitients Insured Uninsured Data Results Total Number of Patients Not Completed Completed Mental & HOPE Team

16 Completed vs. Not Completed Referrals Not Completed Completed Mental & HOPE Team Number of Completed Referrals Within 60 After 60 Average Days Number of Completed Referrals

17 DNKA DNQ Refused Service Referrals that were Not Completed Patient has not been back since initial appointment Reason Unknown Referrals that were Not Completed (Raw Number) DNKA DNQ Refused Service Pt hasn't been back Reason Unknown Referrals that were Not Completed (Percentage) 74.2% 6.3% 10.3% 0.4%8.9% DNKA DNQ Refused Service Pt hasn't been back Reason Unknown Insured vs. Uninsured Patients Total Number of Patients Not Completed Completed Mental & HOPE Team Insured Uninsured

18 Insured vs. Uninsured Uninsured Not Completed Completed Mental Insured % Insured vs. Uninsured 80.0% 70.0% 60.0% 50.0% Not Completed 40.0% 30.0% 79.6% 70.4% Completed Mental 20.0% 10.0% 0.0% 16.3% Insured 23.0% 10.2% 6.6% Uninsured Insured vs. Uninsured Patients Completed Referrals Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral Insured Uninsured

19 60 Insured vs. Uninsured Completed Referrals Average # of Days Insured 16 Uninsured 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 91.7% Insured Insured vs. Uninsured Completed Referrals 8.3% 69.2% 30.8% Uninsured Referrals by Race Total Number of Patients Not Completed Completed Mental & HOPE Team Asian Black Hispanic Indian Other White

20 Race White Other 810 Indian 11 0 Not Completed Hispanic Completed Mental Black Asian % Race 90% 80% 89% 70% 75% 75% 60% 50% 40% 30% 60% 40% 50% 50% 63% Not Completed Completed Mental 20% 10% 0% 25% 21% 14% 11% 0% 4% 12% 0% 0% 11% Asian Black Hispanic Indian Other White Number of Referrals Completed Referral by Race Number of Referrals Average Number of Days it took to Complete a Referral Asian Black

21 Hispanic Indian Other White Race Completed Referrals Asian Black Hispanic Indian Other White Average # of Days 120% Race Completed Referrals 100% 80% 60% 40% 100% 77% 82% 100% 100% 78% 20% 0% 0% 23% 27% 0% 0% 22% Asian Black Hispanic Indian Other White 21

22 Referrals by Gender Total Number of Patients Not Completed Completed Mental & HOPE Team Male Female % 70.0% 60.0% 75.4% Gender 71.0% 50.0% 40.0% 30.0% Not Completed Completed Mental 20.0% 10.0% 0.0% 19.7% 20.8% 4.9% 8.2% Male Female Completed Referrals by Gender Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral Male Female

23 60 Gender Completed Referrals Average # of Days Male 12 Female 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 78.6% 75.0% Male Gender Completed Referrals 21.4% 25.0% Female Referrals by Specialty Total Number of Patients Not Completed Completed 23

24 Surgery Clinical Mental Dental Eye Specialty Eye Dental 5 0 Mental Not Completed Completed Clinical Surgery

25 120% Specialty 100% 100% 80% 83% 77% 79% 60% Not Completed Completed 40% 20% 0% 23% 21% 17% 0% 0% 0% Surgery Clinical Mental Dental Eye Completed Referrals by Specialty Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral Surgery Clinical Mental Dental Eye

26 60 Specialty Completed Referrals Average # of Days Surgery Clinical Mental Dental Eye 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 83% 17% 75% 25% Specialty Completed Referrals 0% 0% 0% 0% 79% Surgery Clinical Mental Dental Eye 21% 26

27 Secondary Care Breakdown of All Referrals Total Number of Patients Not Completed Completed Behavioral Health Cardiologist Colon & Rectal Surgeon Dental Dermatologist Endocrinologist ENT Gastroenterologist Geriatrics Gynecologist Hand Surgeon Health Department Hematologist HOPE Team Infectious Disease Lakeside Behavioral Health Mammogram Nephrologist Neurologist Neurosurgery Obstetrician Occupational Therapy Ophthalmologist Optometry Orthopedic Surgeon Orthopedist Pain Management Physical Therapy Plastic Surgeon Podiatrist Psychiatrist Pulmonologist Rheumatologist Shepherd's Hope Surgeon Urologist Vascular Surgeon Vision Center

28 Secondary Care Breakdown of Completed Referrals Number of Referrals Within 60 Days Number of Referrals After 60 Days Average Number of Days it took to Complete a Referral Behavioral Health Cardiologist Colon & Rectal Surgeon Dental Dermatologist Endocrinologist ENT Gastroenterologist Geriatrics Gynecologist Hand Surgeon Health Department Hematologist HOPE Team Infectious Disease Lakeside Behavioral Health Mammogram Nephrologist Neurologist Neurosurgery Obstetrician Occupational Therapy Ophthalmologist Optometry Orthopedic Surgeon Orthopedist Pain Management Physical Therapy Plastic Surgeon Podiatrist Psychiatrist Pulmonologist Rheumatologist Shepherd's Hope Surgeon Urologist Vascular Surgeon

29 Vision Center Referrals by Age Total Number of Patients Not Completed Completed Mental & HOPE Team & up Age 61-up Not Completed Completed Mental

30 80% 70% Age 73% 73% 74% 60% 50% 40% 50% 50% Not Completed Completed 30% Mental 20% 10% 20% 19% 26% 0% 0% 8% 8% 0% up Completed Referrals by Age Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral & up

31 60 Age Completed Referrals up Average # of Days 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0% 0% Age Completed Referrals 77% 73% 23% 27% 83% up 17% Referrals by Provider Total Number of Patients Not Completed Completed Mental & HOPE Team 31

32 Cadet Lindsey Luciano Torner Torrellas Provider 120% 100% 100% 80% 60% 77% 63% 65% 79% Not Completed Completed 40% Mental 20% 0% 29% 29% 22% 2% 8% 0% 0% 6% 13% 7% Cadet Lindsey Luciano Torner Torrellas Completed Referrals by Provider Number of Referrals Number of Referrals Average Number of Days it took to Complete a Referral Cadet Lindsey Luciano Torner Torrellas

33 60 Provider Completed Referrals Average # of Days Cadet Lindsey Luciano Torner Torrellas 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 79% 21% 71% 29% Provider Completed Referrals 0% 0% 67% 33% 83% 17% Cadet Lindsey Luciano Torner Torrellas 33