Dividing the Diabetic population into Personas
I recently wrote a BLOG entry about personas and their usefulness in User Centric Design. [LINK] Personas are fictitious characters that represent segments of the target population. A persona has the following characteristics: (per usability.gov [LINK])
- a name and picture
- demographics (age, education, ethnicity, family status)
- job title and major responsibilities
- goals and tasks in relation to your site
- environment (physical, social, technological)
- a quote that sums up what matters most to the persona with relevance for your site
Defining diabetic personas is information driven
Research and information drive the segmentation of populations into discrete user groups whose characteristics will affect the design of our solution. I am particularly interested in designing software for self-management and health engagement of diabetes.
Choose which characteristics to segment population with.
Choose characteristics that will affect the design of your solution. Research and information will help determine these characteristics. I did some general reading / discovery and found research that evidenced certain characteristics affecting diabetic rates.
- Age
- Obesity
- Educational Level
- Socioeconomic status (income level)
I then found research from Forrester Research that segments the population at large according to their adoption & acceptance of technology – important for my focus (self-engagement). Forrester calls this Technographic Segmentation, meaning they segment populations based on their attitude towards and adoption of technology. They define 10 specific groups of individuals.
The table below characterizes all potential users of technology into 10 groups based on their attitudes, income characteristics and family status.
From IP Business (refers to the 2007 North American Technolographics Benchmarks Survey):
Segment the population using research:
First I find research that divides the diabetic population into discrete groups / segments. This CDC Document segments the population by age:
Choose a specific group and further refine the segmentation
I am specifically interested in the 40-59 year age group representing 10.8% of the population.
According to the National Bureau of Economic Research, diabetic rates vary according to socioeconomic and educational levels. I’ve summarized their general findings in the two trending charts below, essentially lower income and less education equates to higher diabetic rates.
Education level affects diabetes
Comparing prevalence by education group, the author finds that high school dropouts are roughly sixty percent more likely to have diagnosed diabetes and twice as likely to have actual diabetes as men who have attended college. The improvement in diabetes detection over the past twenty-five years has been larger for college-educated men (from 50 percent of cases undiagnosed to 16 percent) than for high school dropouts (from 49 percent to 31 percent).
Socioeconomics / Income affect diabetes
Further research from BMC Health Services Research concludes:
Low income is associated with a higher prevalence of diabetes and a higher population rate of referral.
The Rand institute reported similar findings [ LINK ]
Obesity increases with lower income / socioeconomic status
Perhaps this isn’t surprising as there are numerous studies that find inverse relationships between income and obesity:
WorldFoodPrize.org : 52% of food insecure (lower income) people become overweight.
This paper by Dr Marguerite Bryan (Xavier University) states: The disease of obesity disproportionately impacts subpopulations of African-Americans/Hispanics, people of lower socioeconomic status and women.
DocShop.com puts it succinctly: Statistics show that low-income individuals are significantly more likely to be overweight or obese than those who are financially well-to-do.
CDC also states: Body weight is the result of genes, metabolism, behavior, environment, culture, and socioeconomic status.
Type II Diabetes rates increase with obesity rates.
Science daily: Obesity is probably the most important factor in the development of insulin resistance
Obesity.org: Carrying extra body weight and body fat go hand and hand with the development of type 2 diabetes
Thus I’m making the inference:
Build Personas from your segmented population:
Forresters Technographic segmentation of the population resonates with me. So I’m going to try and map the diabetic population into Forrester Research’s 10 technographic segments. Further more, I’ll do a bit of hand waving and try to quantify how much of the population is in each segment.
1) I’m focusing on the 40 – 59 year old diabetic population.
2) I’m going to cut that population into Forrester’s High and Low Income earners, of which the low income earners with have a higher diabetic population and higher obesity population (given research above)
3) I’ll then use Forrester’s values to create personas.
Referring back to Forrester’s Technographic table (I’ll provide 2 here, from 2 sources):
Ref: IP Business
- Techno Optimist : High Income Career
- Techno Optimist : High Income Family
- Techno Optimist : High Income Entertainment
- Techno Optimist : Low Income Career
- Techno Optimist : Low Income Family
- Techno Optimist : Low Income Entertainment
- Techno Pessimist: High Income Career
- Techno Pessimist: High Income Family
- Techno Pessimist: High Income Entertainment
- Techno Pessimist: Low Income Sidelined Citizens
Now I’m going to focus in on a select few of these. I’m going to toss 7 & 8 and address them using a persona geared for the 10th segment. Why? B/c 7 & 8 are difficult to address with technology (as is 10) and they are less likely to have diabetes, so by having a 10 persona I can provide tools that 7&8 can use without putting much effort into them. That leaves us with:
- Techno Optimist : High Income Career
- Techno Optimist : High Income Family
- Techno Optimist : High Income Entertainment
- Techno Optimist : Low Income Career
- Techno Optimist : Low Income Family
- Techno Optimist : Low Income Entertainment
- Techno Pessimist: High Income Entertainment
- Techno Pessimist: Low Income Sidelined Citizens
Personas:
1. Jack (Techno Optimist : High Income Career)
- Age: 40-50’s
- College degree (+)
- Single – no kids
- White Collar worker (manager – executive)
- Wants to manage his diabetes given a very busy schedule.
- Has Time for exercise, eats out often.

My career and work activities dominate my life, I need a tool to help me manage my diabetes and help me stay on track.
Likely Technologies:
- PC
- SmartPhone [ IPhone or Blackberry ]
2. Sue (Techno Optimist : High Income Family)
- Age: 45-55
- College degree (+)
- Married w/ kids
- White Collar worker (manager – executive) and parent
- Wants to manage her diabetes given a very busy schedule in a family friendly way
- She has video on demand, net book, a smart phone
- Little time for exercise, has control over meals cooked at home & bought out
My personal time is spent on family matters and my work life is demanding as well, I need a convenient tool to help me manage my diabetes that works around my family and my work.
Likely Technologies:
- PC
- SmartPhone [Blackberry/IPhone] or Cell [SMS]
3. Curtis (Techno Optimist : High Income Entertainment)
- Age: 40-55
- College degree (+)
- Married w/ older kids
- White Collar worker (manager – executive) and parent
- Wants to manage his diabetes in the most convenient way
- Little time for exercise, no control over meals cooked at home and eats out regularly
I enjoy using interactive technology in convenient ways, namely on my PC.
Likely Technologies:
- PC
4. Katie (Techno Optimist: Low Income Career)
- Age: 40 - 50
- Highschool or College degree (+)
- Single no kids
- Low level wage earner – retail, help desk, fringe white collar worker
- Wants to manage her diabetes using new / hot technologies
- Does not exercise often, financial constraints limit control over meals cooked at home and eats out at less expensive restaurants (fast food)
I try to adopt new technologies and want to manage my diabetes using the newest applications.
Likely Technologies:
- PC
- IPhone
5. Suzie (Techno Optimist: Low Income Family)
- Age: 40 - 50
- Highschool or College degree (+)
- Family with kids
- Low level wage earner – retail, help desk, fringe white collar worker
- Wants to manage her diabetes using technologies her family uses
- Does not exercise often, financial constraints limit control over meals cooked at home and rarely eats out.
Our family has a few basic technologies that I can use to control my disease
Likely Technologies:
- Low cost PC
- Gaming console
- SMS
- IVR
6. Drew (Techno Optimist: Low Income Entertainment)
- Age: 40 - 50
- Highschool
- Single
- Low level wage earner – retail, help desk, fringe white collar worker
- Wants to manage his diabetes using entertainment based technology
- Does not exercise often, eats out at low cost restaurants (e.g. fast food)
I use technology for entertainment and want to track my diabetes in the same way.
Likely Technologies:
- IPod
- Gaming Consoles
6. Drew (Techno Pessimist: High Income Entertainment)

- Age: 48-59
- College +
- Married
- High wage earner, manager or executive
- Wants to manage his diabetes but generally dislikes technology except for entertainment.
- Does not exercise often, eats out often at nice restaurants and can afford nutritious food when cooking at home (him or his wife)
I use technology for entertainment but otherwise want to stay away from technology. If it isn’t easy, I won’t use it.
Likely Technologies:
- SMS
- PC (though unlikely)
6. Don (Techno Pessimist: Low Income Sidelined Citizens )
- Age: 40-59
- Highschool
- married or single
- Low wage, blue collar worker
- Wants to manage his diabetes but does not use new technologies
- Does not exercise often, eats at home but financially constrained as to what food he can purchase or at low cost (e.g. fast food) restaurants
I don’t use technology. I have a cell phone and a TV. I don’t use the internet often outside of maybe email.
Likely Technologies:
- SMS
Modern Medicine is in a state of technical antiquity
Over the past week I’ve interacted with our healthcare system in 2 ways:
- Drug test for a new employer at Quest Diagnostics
- Internal Medicine Appointment (Nashville, TN)
I’ve begun to realize just how far we HITmen have to go.
Question Diagnostics:
Though much work has been done by Quest to modernize their offering – integrating with Google Health & Microsoft HealthVault as well as Keas.com, little of that work is “sold” at the point of care offices. All of the technical effort is shoved aside, relegated to office corners, standing up as cardboard kiosks offering colorful brochures.
Like autumnal leaves scattered about the office, the brochures add color to an otherwise drab office but garner little attention beyond a few glances.
I came with a paper receipt, pre-filled out, in carbon-copy triplicate. The Quest tech dutifully tore the sheets apart, filed them in overfilled drawers and shuffled me to the back. I did my duty and was escorted out of the office without any mention of Quest’s technical offerings. Frankly I’m not sure she even had a computer, but I am sure she didn’t know anything about Quest’s many high-tech offerings.
As a technologist, I’m saddened to see so much effort ignored – so much value lost.
Internal Medicine Appointment : Baptist Hospital
I had a 3:00 PM appointment, I arrived at 3:05 PM was called to the back at 3:25 and finally met a doctor at 3:45 PM. Sadly typical, but what amazed me was the state of modern medicine. This is Baptist Hospital in Nashville, TN. The doctor’s office was on the top floor of a well designed, aesthetically pleasant 9 story building that towered over the Emergency Room where my father worked for 25 years as a E.R. Physician. But after my appointment, I wondered if much had changed since my father saw his first patient all those years ago.
The waiting room had modern touches: dark, wood flooring, subtle, ambient lighting, appropriately upholstered and fairly plush seating, but true to my past experience with doctors I received the age old wooden clipboard filled with a small stack of papers asking the same tired questions I had answered over the past thirty years. Age, Sex, Name, Medications, Medical History…
I asked the nurse if they had PHR, EHR or EMR – then I saw the phosphorous green screened machine she punched my credit card into, I was amazed to hear the dot matrix printer produce a double ply receipt -- I received the carbon copy. I shook my head – definitely no EHR or PHR. I explained the difference between the three, the nurse said they had some new software called NextGen (http://www.nextgen.com/), but she couldn’t tell me anything beyond that.
She drew her hand over her head, meaning she didn’t get any of the technical points I was trying to make. So I sat down with everyone else and filled out the forms with a blue, ballpoint pen.
The Technician
Once I got past the waiting room, I was led around by a unenthusiastic technician. I asked how her day was, “okay I guess.” I noticed the Fuji Lifebook she carried, and as she entered my weight (195 lbs – about ten pounds too heavy) I asked her how she liked the software she was using.
She turned the book around and showed it to me. A Windows based application with straight forward forms – 2 ways to enter data: 1) Stylus or 2) Keyboard. Though she used the software without a hitch, she hated it.
“It’s slow. Too complicated. Pens and paper are faster.”
I didn’t try to change her mind; she must have been having a bad day. I kept looking at the software. Hard to say what software package they were using, but I’d imagine it was Enterprise Practice Management:
NextGen EPM can centralize appointment scheduling, billing, collections, and other business processes for group practices, while preference settings allow different locations, and in some cases staff, to operate according to their own workflow.
Workflow flexibility is the key to productivity. Yet, management can control business processes across practices because data is collected and centrally stored in a standardized, discrete format.
This gives practices real-time access to patient records from any location, to reduce redundancy and errors – and to provide patients with better service. At the same time, managers have instant access to reports, for financial and operational analysis, that are built into the system.
NextGen EPM features other practice-configured automation tools for increased productivity and management control, such as WorkLog Manager and Autoflow, a computer-guided check-in/check-out process.
NextGen is more than vendor – we are your partners in the development and growth of your group practice. When you collaborate with NextGen, you benefit from our:
- Customized workflow that is uninterrupted, as standardized, discrete data is collected for pay-for-performance, business analysis, audits, outcomes analysis, and more.
- Single-vendor solution for integrating your administrative and clinical processes on one system for streamlined, consistent patient care.
- Stability as the most financially secure, publicly traded (NASDAQ:QSII), company in our market space, with over a thousand employees and growing.
Waiting for the Doctor
I waited in a patient room for twenty minutes. Frankly I could have used a bit longer to take in the sheer antiquity of the place. The walls were brown with a dark brown trim and dark oak doors. A mercury filled blood pressure cuff hung from the wall like a historical relic, but the technician used it ( 120 / 80 – good I was told ). A white melamine storage cube stood over an old, worn gray bed with crisp white paper covering the creased and cracking plastic cover.
The whole room felt old and out of place. The clean white linoleum floor looked sterile, the room out of some forgotten time. There were no modern amenities. Everything in that room could have come from the 80’s or 90’s – nothing hinted at the 21st century. Even the off white, plastic phone that hung on the wall communicated one thing: Modern Medicine lived in a strange reality unaffected by technical change.
In Healthcare IT we obsess over security and privacy, but those ideas were as absent as interior design. The walls were paper thin, and even the leaky faucet with its persistent drips couldn’t compete with the candid discussion going on in the next room.
The conversation was morbid, depressing – literally. The doctor advised his patient that Valium could not be used to solve anxiety in the long term. The patient discussed her bouts of depression. The doctor asked if she’d considered suicide, and she indicated there were episodes of depression in her family but that’s as far as it had ever gone.
I wasn’t prying. The conversation was loud, for a moment I thought amplified. I couldn’t ignore the conversation, they might as well have been in my room. Thankfully my doctor came in before the prognosis next door got any worse.
Meet My Internal Medicine Doctor
He was older, in his sixties, he had the same gate and demeanor as my father. He held his Fuji laptop and stylus in the same way that he had held a clip board and pen over the past thirty years. I asked him what he thought about the NextGen software, and he showed it to me with deliberate patience. He picked at the screen and navigated the forms, but he smiled when he said “I’m from the old guard. We don’t get used to computers easily.”
But he liked the software (EMR), not for the reasons that he should – for the value that we in IT should provide. The software didn’t help with the diagnosis or suggest tests or even provide an optimized, world class workflow.
My doctor admitted that this is the way of the future, but I was more interested in why?
- No more lost charts
- No illegible notes
To him NextGen was merely the next generation clip board. I smiled looking around that old room, at his well worn, wrinkled fingers as they hunted one key after another. Beyond that laptop, the only thing indicative of the 21st century was the the Sports Illustrated sitting on the windowsill – November 2009 edition. I walked out of that anachronism and into the modern world realizing just how far we HITMen have to go.
In the Media: NY Times { EMR No Measurable Benefit }
http://www.nytimes.com/2009/11/16/business/16records.html?_r=1
A new study comparing 3,000 hospitals at various stages in the adoption of computerized health records has found little difference in the cost and quality of care.

