FAQS for FOTO:

We love questions at FOTO! Here are a few recent questions and their answers. If the answers are not satisfactory, please contact us directly.

Question:  What items are asked?

Response:  You can obtain a list of items asked by calling Judy Holder at the Knoxville , TN office. However, as we progress with the Item Response Theory process and expanding item bank, the list of individual items will become too long to send practically. Ask for a CD of the new software, from which you can see the items we ask.

Question:  We have concerns for patient self-report of data compared to clinician assessment of outcomes data.

Response:  Patient self-report is a concern for many people, but the history of patient self-report of health status data is very sound in the scientific literature. For example, see the supplement of Medical Care 2000 vol 38 no. 9 supplement II, which is a collection of papers from the by invitation only conference on health status conducted by AHRQ in 1999. See also McHorney CA. Generic health measurement: past accomplishments and a measurement paradigm for the 21st century. Ann Intern Med 1997; 127:743-750 for one of the best historical reviews of the process of collecting patient self-report of data.

Most peoples' concerns about patient self-report of health status information centers around reliability and validity of the data collected. We have the reliability data for our system (several papers in the FOTO papers list), and it is identical to the published reliability statistics from John Ware and others. So, the measures we collect from our process are reliable (See Patient Self-Report Reliability and Validity White Paper).

Validity has been published as well. There are differences in outcomes by acuity, age and severity which also support validity. So, the measures from our process are valid, as they are from the SF-36 and other well designed condition specific surveys (See Patient Self-Report Reliability and Validity White Paper).

Most social scientists favor patient self-report over clinician assessments of function, particularly for change in function, because there is a potential for incentive driven bias from the clinicians.

We are now attempting to account for that difference by assessing global change from the patient's perspective and therapist's perspective, independently. We'll let you know what our data says!

We are also excited about adding clinician-generated measures of patient function. We are exploring some evolving measures that have good psychometrics.

So, the FOTO system is reliable and valid. That is published and more papers are in the works supporting the psychometrics of our tools. There should be no concern for CMS or other payers on a scientific account.

Question:  How do you compare your data to data from patients not using the FOTO system?

Response: Difficult to address the issue of comparison of others who are not in the FOTO system. Unless the comparison group is asked the same questions, then the best you can get is a relation between differences (magnitude and direction) in our measures vs. the comparison measures. Have not conducted that analysis, yet. We are interested to do just that, though!

Question:  Please describe the FOTO database.

Response:  The FOTO database is the largest outpatient database in the world that tracks change in patient self-report of functional status. There are over 1,600,000 patients entered from over 1,500 clinics and over 12,000 clinicians since 1992. Our primary interest has been functional status, but other constructs are now being collected, like self-efficacy, pain, etc.

Question:  How does FOTO check the quality of data being entered into the database?

Response:  FOTO checks the validity of the data as best we can. One never knows if the answer to any question is the truth, if the person understood the question, if the person made a mistake responding to the question, etc. However, we have tested data entry validity many ways, and the results support that 90% of patients (n>75,000) have no clinical inconsistencies in their responses at intake, and 96% of the patients have no inconsistencies at discharge.

Interestingly, when we follow those patients who we clinicians believe answered the questions with some clinically logical inconsistency, those same patients invariably answer the same question the same way at discharge! The probably of this happening by chance is very low! This implies we clinicians don't really know what our patients are thinking or perceiving about their disabilities! That is supported by other non-FOTO literature.

In our new CAT process, the computer checks the responses each patient provides in real time! The CAT is based on conditional probabilistic models, so the computer checks the observed response against the expected response and identifies the unexpected response for the clinician on the patient specific report in real time. The clinician can then evaluate the patient accordingly. We are programming PI right now to re-ask the question to which the patient provided the unexpected response. So, shortly, the computer will take a very active roll in checking the validity of the patient response.

No clinician-generated measure can boast the same validity check!

Also, we set the level of precision the computer will accept a priori! So, the computer will not stop asking questions until the precision of the functional health status measure is better than the best condition specific tool currently in print! We set our CAT to be the best...

Question:  Can FOTO separate patients by payer?

Response:  We can easily separate patients by payer, like Medicare. Therefore, you can estimate many variables by payer, including fee-for-service (indemnity), litigation, PPO, HMO, Medicare A, Medicare B, Medicaid, workers’ compensation, patient private pay, and other. Other common variables include but are not limited to outcomes, visits, duration, value, patient satisfaction, risk-adjustment variables, etc.

Question:  Can we identify patients, clinicians or clinics in the FOTO data set, so we can match them to our database for comparison?

Response:  To personally identify FOTO clinics, patients, clinicians, etc. so you could compare your data with FOTO's data, we would need to address confidentiality. We would have to have any project of this nature approved by our and possibly your Institutional Review Board for the Protection of Human Subjects and get all the necessary informed consents.

Question:  How do you protect against clinicians selecting the patients they want to enter into the FOTO database?

Response:  We direct all our customers to enter all of their appropriate patients into FOTO, but there is no check for whether they do. Therefore, we have to assume there is some patient selection bias in the data from patients that come in at a busy time and the front desk misses them, or many other legitimate reasons. That is the implementation rate: what percent of patients who are appropriate for FOTO actually get into the FOTO database. We do not know that number.

On the other hand, the completion rate, or the percent of patients who enter the FOTO system who actually get discharged successfully is about 70%. That is quite high for this type of data. We are proud of that completion rate. We want it better, but we'll take 70%!

Question:  Which payers are identified in your database?

Response:  Our data comes from many payers, but don't know if that includes "all payers". Customers identify the payer for each patient as fee-for-service (indemnity), PPO, HMO, workers' compensation, litigation, Medicaid, Medicare A, Medicare B, patient private pay, and other.

Question:  What is the average age of your patients?

Response:  The average age for all patients is now 49 (SD 16, range 14-102 yrs) years. Was 45 yrs only five years ago!

Question:  How do you address confidentiality of your data?

Response:  We address confidentiality issues by maintaining strict policies and procedures and implementing HIPAA requirements. Customers sign a contract with us, and we do not disclose the identity of patients, clinicians or clinics. If we want to identify clinics or clinicians, we need their written permission. We never disclose the identity of patients except to the clinicians who treated them, ie for auditing purposes. We have an extensive method of destroying written patient surveys, managing the electronic data, etc. Limited numbers of people have access to data with patient identifiers. All electronic access to the data is audited. Several firewalls protect access to data. Patient signed consent is recommended to the FOTO customer, but we do not monitor their compliance. A complete set of data confidentiality policies and procedures can be obtained from Ben Johnston, at the Knoxville office.

Question:  Does FOTO track or study outlier patients?

Response:  We can look at the outcomes and other data from outlier patients. Outliers are commonly identified for customers, so the customer can audit their medical records as part of customer continuous quality improvement processes.

Question:  Does FOTO predict visits, duration, outcomes, etc?

Response:  We can predict number of visits, duration, cost, outcome, etc. for patients in a risk-adjusted manner routinely. The data necessary for this prediction is a normal part of the quarterly report to all customers.