If you want to be a leader, you need this “X factor”​: Executive Presence

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The “X” factor: Executive presence distinguishes leaders from the crowd of people with mere talent or merit.

First named and described by Sylvia Ann Hewlett, EP is:

“… an amalgam of qualities that true leaders exude, a presence that telegraphs you’re in charge or deserve to be. Articulating those qualities isn’t easy, however.”

Success does not naturally follow talent and hard work. There are studies in support. You need to have extra qualities that are not easily acquired, and can even be hard to pin down. The most well known is Daniel Goleman’s description of Emotional Quotient (EQ).

3 Qualities: EP is a mix of 3 elements.

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1. Gravitas: confidence + poise under pressure + decisiveness. This is the defining characteristic of leaders and is easily the most important.

2. Communication skill: speaking skills + deep, close listening + ability to read an audience or a situation. A powerful vocabulary needs to be a part of the territory. There is a direct correlation between vocabulary size and rank on the corporate ladder. Leaders have a much more powerful arsenal of words than those lower in the hierarchy and know how to tailor them to the audience at hand.

3. Appearance: Although not as critical as the other two, it completes the overall effect. A scruffy, distracted appearance does not go down well.

In addition, there are 3 more elements that complete the picture.

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1. A calm demeanor: Tantrums and prima donna-like behaviour turn people off. You may be a genius and endowed with rare abilities, but you are unlikely to be a leader if you can’t keep a firm grip on your emotions.

2. Self-awareness: Leaders are aware of their own limitations. They are not afraid to ask for help when they are out of their depth. They delegate effectively.

3. Getting things done: They strive for and achieve completion in all of their tasks. They don’t leave situations hanging and unresolved.

Next time you come across someone who is “charismatic”, use this EP list to see how many of the boxes they check. Ask yourself how you can build it into your persona. Executive presence is not an inborn gift. It can be learned and implemented.


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Pay it forward – be a mentor

Photo credit: Image by Sasin Tipchai from Pixabay

The Buddha constantly emphasised that the attainment of enlightenment was not the end of the spiritual journey but merely the beginning of a duty: the unremitting responsibility for providing counselling and solace to those in need of help for their prevailing predicaments (Dukkha).

In a professional context, and in a word: mentorship.

Paying it forward: Traditionally, we look at paying back as the way of acknowledging help and support given to us in times of need. There is a more effective alternative: paying it forward. In gratitude for what was received, we should consider helping others in need. The downstream benefits and multiplier effects are much greater. That’s what mentorship is all about.

“. . . a great mentor can provide a path to finding your own true answers.” Tina Turner quoting Miles Davis, the jazz legend.

Coaching differs significantly from mentoring. It is often short-term, well-structured, and designed to achieve specific, tangible outcomes. A coach is the least personal relationship option.

“Searching for a mentor is similar to searching for a spouse: you two need to share common values, concerns, experiences, communication style, and, of course, have time to invest into meaningful conversations with one another.” — [Anna Szabo, Turn Your Dreams And Wants Into Achievable SMART Goals!

An ideal mentor should be:

  • Accessible: there when needed.
  • Experienced: been there, done that.
  • Well connected: knows someone . . . who knows someone.
  • Tough but empathic: iron hand under a velvet glove.
  • Enthusiastic: yes, you can do it!
  • Charismatic: wow factor.

The scaffolding of good mentorship

  • Recognise what you desire from the relationship. It’s crucial to keep in mind that mentorship is a relationship. Instead of jumping right into business, the most effective mentorships are those in which the mentor and mentee take the time to get to know each other and grasp each other’s viewpoints.
  • Set expectations together from the start. How long do you want the mentoring to continue (but you may always extend it if you both believe it’s beneficial). Define critical objectives for your mentee to attain. Work together to build a general idea of how your meetings should go. Make certain they are focussed on a few essential problems.
  • Take a genuine interest in your mentee as a person. The cornerstone of good mentoring is empathic listening.
  • Develop a sense of trust. Trust takes years to develop, yet it can be shattered in an instant.
  • Don’t make assumptions about the mentee – inquire. Age, gender, colour, physical habitus, and appearance are seldom reliable indicators of what lurks underneath. Find out what makes the mentee tick by talking to them.
  • Share your experiences. It can provide you with a unique perspective on the challenges your mentee may be dealing with. You could have had a similar situation, so now is a wonderful opportunity to share what you went through and how you dealt with it.
  • Look for resources to help your mentee. This is where mentors can make a real difference. You’ll have insider knowledge of the area and access to resources that your mentee wouldn’t be able to obtain on their own. Link them to these resources.
  • Be aware of your limits. When your bandwidth is limited, admit your lack of expertise and recommend other sources or persons.

Anyone can be a mentor: The image of a mentor is often one of leaders, who have been sharpening their skills for years and are experts at what they do. However, that’s not quite true; you can be a mentor if you are enthusiastic and willing to share your experience with others!

Virtual mentorship

Post-COVID, remote work is now firmly entrenched as an alternative for providing professional services. Many individuals believe that physical closeness is necessary in developmental connections such as mentorship. This is wrong. However, mentorship is characterised more by the results achieved than by the medium by which it is carried out.

  • Plus: Virtual mentoring may be more egalitarian since visible status signals signifying organisational position and physical stature are reduced to a voice and a screen of equal size in video-based talks.
  • Plus: The limitations of shared space and location are also removed with virtual mentoring. Mentor/mentee schedules and locales are more flexible with online choices.
  • Minus: Because the whole spectrum of nonverbal signs and vocal subtlety may be lacking, it may take more work to create trust and rapport in the relationship. Virtual mentoring, like many other online partnerships, may suffer from email overload and screen weariness.

“I knew from my own life experience that when someone shows genuine interest in your learning and development, even if only for ten minutes in a busy day, it matters.” — Michelle Obama, Becoming


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The secret sauce for “Getting Things Done”: slow down

The claim, “I’m busy,” is flaunted as a badge of honour. But, are you getting things done? Is your health and personal relationships suffering from your busy-ness?

There is a better approach to success and productivity: “slow work.”

“Restore your attention or bring it to a new level by dramatically slowing down whatever you’re doing.” —  Sharon Salzberg, Real Happiness: The Power of Meditation

  • Dismount the treadmill: We get stuck in the cycle of prioritising the urgent over the important. You have to step off and reverse the choices.
  • Single-tasking: Set aside time to focus on a single activity. If the job is complex, break it down into smaller, simpler chunks. It’s useful to work in 20- to 30-minute sessions with short breaks in between. If you are stuck, listen to music, take a short walk–break the rhythm.
  • Use the Pareto Principle (80-20 rule): 80% of our outcomes originate from 20% of our efforts. Invest time in understanding the activities that have the “greatest bang for the buck” and focus your energies on them. This will help you transition from a hustling attitude to a leisurely work philosophy.

Decision making has speed limits

In today’s world, much of our daily efforts involve decisions. If you are hoping to hasten your decision-making, forget it. You can’t ramp up the speed of your thoughts no matter what you do or how hard you try. Your thinking rate is fixed.

Some guidelines for good decision making

  1. Concentrate on what you really want. Ask yourself, “What do I intend to accomplish by addressing this choice?” Look at the answer from a 360 degree perspective.
  2. Don’t get caught up in little details. Leave them for later, when you are actually executing the task.
  3. To avoid decision-making under pressure, pre-commit to strategies that you have thought out ahead of time. 
  4. Seek the opinion of others. Obtain a few perspectives, preferably from those who have past knowledge of the subject.
  5. Be aware of your emotions. Don’t let anger and other negative feelings push you.
  6. Write down your ideas and options to help you clarify your thinking.

The quality of your judgments suffers when you are under pressure.

If you want to make better decisions, you need to do everything you can to reduce the pressure you’re under. You need to let your brain take all the time it needs to think through the problem at hand. You need to get out of a reactive mode, recognise when you need to pause, and spend more time looking at problems.

Make judgments while sitting down and examining the subject from several perspectives. You’ll still need to set aside time to do nothing but ponder.

The merits of slack time

Slack is the lubricant of change.

We are brainwashed by the belief that continuous activity equals efficiency. A lot of this perceived busyness is spent in the pursuit of trivial, unimportant tasks. In order to be effective, a certain amount of wiggle room is mandatory.


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Want to be more empathic? Try listening with your eyes closed

This is how the Japanese listen to speakers. When someone addresses a group in Japan, the audience will shut their eyes and listen with their heads bowed. They are focusing on the Hara, an energy field that is centred around the navel of the abdomen. This response can be extremely disconcerting to outsiders who are invited to talk and are unaware of the practice.

There is a lesson to be learned from the Japanese about the skill of listening with empathy.

Skills can be hard or soft. Hard skills can be made explicit and overt, taught and passed down hierarchies with relative ease. Apprenticeship remains the major route for acquiring hard skills.

In earlier times, you could thrive on your hard skills alone. You could be rude, gruff and inhospitable, but the world would beat a path to your product. Not so any more.

Soft skills are vital in an age where technology is usurping and executing physical tasks. Soft skills are tacit — much harder to teach and certify. There are varying degrees of difficulty in the quest to acquire them. Indeed, there are some that can’t be taught; empathy may be one such.

Humans are social animals. Except for the occasional hermit, we need contact with our fellow humans on a regular, sustained basis. From an evolutionary standpoint, this makes perfect sense: connected groups have a better chance of survival than solo artists. Many people, even though they have strong feelings about wanting to connect with others, have problems with social connection and understanding.

Communication skills head the list of useful social soft skills. This is the age of networks where persons who are most valued and respected — influencers — are those who are deemed to be good with people at all levels, not tied down by rigid hierarchies and social strata.

  • Listening skills are very important tools for being a good communicator. Empathy — the ability to feel another person’s emotions, particularly pain — is the cornerstone of good listening.
  • Humans have an impressive array of tools for expressing and perceiving emotions. Body language and facial expressions are two traditional outward manifestations that can be read by listeners. They can often convey more messages than words.
  • Nevertheless, the spoken word is the cornerstone of communication. The voice is a particularly powerful channel for expressing emotions. In addition to the linguistic and content elements of speech, there are “paralinguistic” vocal cues that may provide effective pointers to underlying feelings which impel the words. These include volume, pitch and cadence.

Empathic accuracy is a skill with which individuals can effectively judge the emotions, thoughts, and feelings of others.

In 2017, Michael Kraus from the Yale University School of Management published a very intriguing piece of research. The study was carried out with 1772 participants. The central prediction tested in these studies was that voice-only communication enhances empathic accuracy relative to communication across senses. In other words, shutting off sight could enhance empathic accuracy.

The data showed that voice-only communication elicited higher rates of empathic accuracy relative to vision-only and multisense communication, both while engaging in interactions and perceiving emotions in recorded interactions of strangers.

  • Voice-only communication is likely to enhance empathic accuracy by increasing focused attention on the linguistic and paralinguistic vocal cues that accompany speech.

It seems as though the advice to listen with your mouth shut needs to be extended to the eyes as well!

Reference: Voice-Only Communication Enhances Empathic Accuracy. Michael W. Kraus, Yale University, School of Management, American Psychologist 2017, Vol. 72, No. 7, 644–654

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A Walk Through the Brave New World of Healthcare Data Analytics

With a stethoscope around the neck, a good flashlight, thermometer and genuine empathy for patients, you were all set to go as a doctor, just a few decades ago. The need for empathy remains, but the world of healthcare delivery has changed hugely since then.

Fast forward to today. Sci-tech has given us tools of remarkable capability. There is no corner of the human body, however small or remote, that cannot be imaged, measured, probed and altered in some fashion. We are armed today with devices that can even work upon the very stuff of life and creation: DNA. The words of the science fiction writer, Arthur C Clarke, come to mind: “Any sufficiently advanced technology is indistinguishable from magic.” What modern Medicine can deliver today is undoubtedly magical.

From Pieces, Into Bits — the Digital Transformation

In keeping with all other areas of human activity, the years have seen a shift in medical technology from analogue to digital. As an example, imaging studies are almost all captured in digital form. The old x-ray film is now obsolete. This change is convenient; reporting, viewing, archiving, transferring and analysing are all made much simpler with digital systems rather than physical.

The Data Tsunami

The power comes with a price. The data that pours in from any given patient is vast. Everyone dealing with healthcare delivery — users, caregivers, administrators or third-party payers — struggles with the effort of staying afloat in this deluge. Making sense of all this information is a task that can exceed the cognitive abilities of the smartest. It’s now an uphill task to stay up-to-date even in narrow specialities.

Looking at just one speciality, oncology (2005 – 2015):

  • 140 million patient encounters,
  • Generating 0.1 – 10 GB of data per patient (14 – 1400 TB overall)
  • 80% of which is unstructured.

An average hospital generates 665 TB of data, yearly. The quantity is doubling every two years.

A Triple Whammy

Three properties characterise the data deluge.

  1. Volume — as exemplified earlier.
  2. Velocity — the rate of accrual and change is estimated at 20 – 40% per year, meaning that the size of the data store doubles every other year.
  3. Variability — Captured data is stored in silos that can be difficult to penetrate. A large part of the problem is the lack of unified data storage structures and inter-operability. On top of all this, a substantial portion of the data resides as unstructured records, often descriptive text and narratives.

Tunnel Vision versus Big Picture

As a result, it is challenging for anyone — users, caregivers, administrators or payers— to get “the Big Picture”. Like the story of the blindfolded men encountering an elephant, each one interprets the whole through the narrow lens of what is immediately perceivable by the remaining senses.

New Wine, Old Bottles

Fortunately, the very same technology that has brought about the problem also can provide solutions. Data analytics is the hottest ticket in today’s information technology scene. Data mining, machine learning, deep learning and artificial intelligence offer us the means to make sense of this mass of bits and pieces in a way that individuals — even large teams of people — cannot.

Big data analysis has been a part of managing efficient businesses for some time now. We can extend the lessons learned from business into healthcare delivery to the great advantage of all —- users, caregivers, providers and payers.

Meanwhile, Behind the Scenes

While this flood has been building up, a paradigm shift is ongoing in the way quality healthcare delivery is assessed. For decades, the model of payment in healthcare was “fee-for-service”. Whether the outcome was good or bad, a service was appraised as being worth a specific sum of money and the amount released to the provider.

In recent decades, quality assessment has shifted from a physician-centric approach to a patient-centric one. The endpoint for satisfaction is an outcome that the patient feels is worth rewarding. Life and activities of daily living have been changed for the better (or at least, not worsened) by the transaction. The two points-of-view are, quite often, tangentially opposed.

A “pay-for-performance” model is slowly replacing fee-for-service.

This new model demands a panoramic view of service provision where the individual is compared against a population-based norm. The data keeps shape-shifting and has to be evaluated in real-time from the perspective of the 3 Vs: volume, velocity and variability. Humans can’t do this with ledgers or even spreadsheets. Big data analytics is the need of the day.

Promises to Keep

The intention to harness big data can be sincere, but the tools cannot be wished into existence. There is no magic wand. Starting from a well-organised assessment of needs, healthcare analytic systems have to be carefully designed and implemented. It’s all too common to take a “kitchen sink” approach to the exercise and end up with a product that no one likes.

The Winners

Healthcare data analytics will benefit four groups.

  1. Patients will receive the best quality of care.
  2. Professionals (caregivers) can deliver the best quality of care.
  3. Providers (hospital administrators) can assure users of getting the best quality of care.
  4. Payers (third-party agencies) can be confident in getting the best value for money.

Let’s take a walk through the garden of possibilities.


Data Sources

Where does this mass of information come from? Every aspect of healthcare delivery is today, a geyser of data.

The Patient Record

The patient record is the cornerstone of high-grade medical care. It’s where the process of data analysis begins.

The history and physical exam report is the core component. This document maps the patient’s current and past health status in great detail. Personal habits, past illnesses, family and social history, medications, and treatment plans enter the archive.

Other details are appended over time. They include:

  • lab summaries,
  • treatment plans,
  • procedure notes,
  • nursing notes,
  • medication records,
  • progress notes,
  • consultation requests.

Over time, the repository can become quite sizeable and bulky. Making meaning out of the record becomes a laborious and frustrating endeavour.

The Electronic Health Record (EHR)

The traditionally paper-based record is now captured digitally as an electronic health record (EHR).

EHRs have many advantages over paper.

  • They don’t need the vast spaces that physical records demand.
  • Multiple users can view them at the same time, from different points of the hospital.
  • They can be transmitted anywhere in the world.
    • Most of all, being digital, they lend themselves to data analytics.

The push for widespread EHR usage in recent years has led to the availability of an extensive database which, after analysis, may be repurposed as information packets directed at improving patient care.

There is data in plenty and, of concern, just as many standards for defining the record structure. Any given piece of data may be stored and coded in any number of fashions, often with the same package.

Other Hospital Data Sources

Modern healthcare delivery is a comprehensive, diverse, complex system, probably more so that any other activity in everyday use. Every element of this system pours in data which needs to be factored into the care of a patient.

Some typical sources include:

  1. Laboratory Information Management Systems (LIMS): The number of tests available for clinical use run in the hundreds. Starting from collection of samples from the patient to transporting them, processing them in highly sophisticated machines, reporting results and delivering reports back to patients and care providers, there are numerous points of data collection.
  2. Diagnostic Procedures: There is an equally large number of diagnostic procedures used today. Most of them are now capable of recording the entire transaction digitally. ECG, X-rays, scans, endoscopic tests, angiograms: every one of them can be piped into the data backbone of a hospital.
  3. Monitoring Equipment: The mandate for high standards of patient safety and outcome results in the need for intensely monitoring patients during their journey in a hospital. Multi-channel monitors, alarms, respiratory support devices and many more are data points.
  4. Wearable health devices are here to stay. Immense amounts of personal information are pouring in every day. We have access to perspectives of any persons’ health in a manner never imagined before.
  5. Pharmacy Management: Beginning with simple records of prescriptions, pharmacy systems offer an opportunity to keep track of the complex interactions between drugs and quality care.
  6. Scheduling Patient Flow: A hospital sees large movements of people in and out of the system: appointments have to be made, patients tracked during their journey from area to area, beds allocated to the satisfaction of the patient and the doctor. Computer-based systems coordinate these functions today. They are no longer hand done. Once again, tons of data.
  7. Radiofrequency identification (RFID) is increasingly integrated into healthcare to provide real-time management, tagging, and tracking of patients and staff
  8. Insurance Claims/ Billing: The entire process is now done online. The life of an institution hangs on the efficiency of financial management.
  9. Human Resources and Supply Chain Management—many healthcare organisations now use enterprise-level systems to manage the complexity of care in modern hospitals.

This list merely skims the surface of all that is available. Suffice it to say that modern healthcare delivery pivots around data management.

Meet the Data Scientist

We are now at a point in time where the 3 “Vs” of data which we talked about have to be tamed and converted into useful, actionable packets. The complexity of the task has led to the evolution of a distinct brand of information analyst: the data scientist.

They are highly skilled, specially trained, much-in-demand professionals who are a single-point resource for managing, analysis and interpreting Big Data. They have the capability of using tools that are in themselves complicated bits of engineering.


The Upside

I: Patients

Medical practice is, in its entirety, directed towards the welfare of patients. Let’s see how data analytics can improve what is delivered.

A: Chronic Disease Management

Patients diagnosed with chronic non-communicable diseases (NCD) consume a substantial portion of health services. A handful of specific conditions like diabetes, high blood pressure, heart disease and respiratory disorders account for a major share.

Cost-effective management of NCDs hinges on the ability of providers to pre-empt high-impact, high-cost complications which often occur in patients with these disorders.

NCDs, usually life-long afflictions, provide a wide window of opportunity for applying health care data analytics. The number of data points that need to be weighed and acted upon in each patient can overwhelm the cognitive capacity of the most well-informed, conscientious doctor.

Using smart devices, RFID-embedded machines and the universal availability of mobile telephony, patients can be closely monitored for specific target levels such as vital signs, oxygenation, blood sugar, glycosylated hemoglobin, blood pressure and many more. Detection of abnormal levels or worrisome trends permits early, evidence-based intervention which can slow down the rate of progression of many of these disorders.

Treatment can be personalised and tailor-made to fit the demands of each patient.

In a review of 49 studies of chronic disease management (Bhardwaj et al, 2018), big data analytics was beneficial in:

  • risk prediction,
  • diagnostic accuracy,
  • patient outcome improvement,
  • hospital readmission reduction,
  • treatment guidance and
  • cost reduction.

Population Health Management using predictive analyses has shifted the focus of Public Health from the traditional wait-and-watch approach to prediction and prevention.

B: Genomic Medicine

Genomic Medicine has changed the face of medical practice. Patient genotypes can provide pointers to the most effective drugs and treatment regimes, risk of complications and long-term outcomes.

The discipline is expanding at a breakneck pace. New information pours in every day. Genomic data has to be matched to the vast amounts of values observed for individual patients: a daunting task. The field is wide open for application of data analytics.

 

II: Professionals (Care Providers)

Although the doctor continues to be at the centre of healthcare delivery, modern medical practice is a collaborative effort involving many highly trained and certified providers: nursing professionals, pharmacists, physical therapists, social; workers to name a few.

Data analytics bears great promise for enhancing the skills of care providers.

A: Pre-empting acute/ critical events

As discussed earlier, predictive algorithms can point out and highlight patients with chronic disease who are at risk for crisis situations. Interventions can be made before a patient’s condition snowballs into an acute crisis requiring emergency department visits. Data analytics can identify such high-risk individuals early. Ongoing progress can be monitored, and customised care plans put in place.

B: Learning Health Systems

The information base of healthcare delivery is expanding and changing so rapidly that conventional learning tools like textbooks are obsolete almost from the time of publication. Medical information has to be far more dynamic and real-time.

Data analytics offers tools for designing and implementing “learning health systems”. Every patient visit is an opportunity to both learn and generate new knowledge. Knowledge bases can be looked up to provide the most current evidence. Recommendations can be matched to a patient’s specific data set. New patient information can be added to a global database and analysed on the fly.

Personalised Medicine is the mantra of the day.

C: Research

Data mining tools can pick up patterns that are not easily seen by humans. As data accrues, the analytic engine can keep sniffing out many gems of information and new knowledge. Some examples:

  • Risk assessment
  • Early detection
  • Epidemic detection
  • Potential cures
  • Quality of life improvement
  • Prevention strategies

The COVID 19 pandemic has shown us numerous instances of data analytics picking out potential treatment modalities.

 

III: Providers (administrators)

Hospital administrators are under constant pressure while performing the difficult balancing act between quality and cost. Despite its undeniable benefits to other business domains, healthcare has been slow, even reluctant, to adopt practices that are of proven value in business. The post-Covid years are sure to see notable changes in healthcare delivery methods. The role of data analytics will be crucial to survival and staying afloat in what promises to be a highly competitive arena.

Here are some critical areas where data analytics can find an application.

A: Key Performance Indicators (KPI)

Every process offered in healthcare has an outcome. Both process and outcome can be objectively assessed, tracked over time frames and outcomes compared against established norms or over changes in time within a given provider’s domain. This is a KPI.

Any number of KPIs are in use. Some common examples include the length of stay (LOS), 30-day readmission rates and healthcare-associated infection (HAI) rates.

The variables (process(es), factors) underlying each outcome can be complicated. Making associations between intervention and outcome can’t be done manually. Multi-factorial analysis of massive data requires data analytic tools.

KPIs can be keyed into performance dashboards (see below). Feedback to caregivers, when done in a sensitive, non-punitive manner, can be powerful tools for quality improvement.

KPIs can be used to set up “best practices” manuals that could be highly specific for a given institution.

Even with clear goals in mind and a manageable list of KPIs, the process gets very foggy when large volumes of data are involved. Enter, data analytics.

30-day readmission rates

30-day readmission rates are an important KPI of quality of care. Hasty discharges before adequate stabilisation of patients often result in readmissions within a few weeks.

These events lower patient satisfaction. Outcomes are often adverse. Hospital costs climb steeply. Payers often impose penalties on providers for this complication.

Data analytics give valuable insights into the mechanisms that could have been responsible for this event. Corrective measures and policy changes could be implemented.

B: Patient Traffic Flow Management

There is a constant movement of patients and personnel, both into and within a hospital. For long periods, this flow has been managed by personnel who acquire skills on the job, without any formal training in operations management. Considering the intricacies of patient movement in a modern hospital, data analytics can be handy for smooth service delivery.

Waiting time is a leading cause of patient dissatisfaction. Quite often, appointment times are delayed by long periods. Patients who need elective admission often simmer in lobbies till rooms are ready for occupation. The average waiting time in an emergency room is about 4 – 6 hours.

Radiofrequency identification (RFID) is a useful option for tagging and tracking patients and staff. Patient’s can be pinpointed with accuracy. The data is valuable for shaping patient flow in the care process. Once again, data analytics offers solutions for optimising and managing hot spots related to patient movement.

C: Billing and Finance

However competent the caregivers, efficient financial management is vital for organisations to stay afloat.

Key Performance Indicators (KPI) can be handy for finance managers. A variety of metrics are available from organisations like the {Healthcare Financial Management Association (HFMA)

Data analytics can provide up-to-the-minute assessments of the financial health of a hospital.

D: Human Error

Adverse events during healthcare delivery are commonly due to human error. Failure to note abnormal values, improper medication administration or misidentification of patients are all too common.

Data analytic systems can spot these events and issue warnings.

 

IV: Payers

Third-party payers usually make healthcare payments in modern practices. Be they governmental organisations or private insurers; they are always battling costs and seeking to get the most value for money.

Data analytics are vital tools for payers.

A: Comparative Analysis

Data analytics permit payers to survey the market for costs and effectiveness of specific disorders and interventions. They can be done both within an institution and between hospitals. Device and procedure costs can be compared.

Pricing data can be mapped against quality outcomes to identify the best quality, lowest cost providers. This data can be used to leverage prices with hospitals carried by the payers.

Once again, data analytics can provide detailed, up-to-date figures.

B: Fraud Prevention

Suspected fraudulent claims can be investigated with data analytics. Comparisons can be made for similar claims at other hospitals of known quality and integrity. Hard data can support rejections.


Dashboards and Displays

It’s not enough to capture and process data. Actionable information has to be displayed to users in a fashion that is easy to grasp. Anyone who has played video games will know that current-day computer graphics is more than up to the task.

The Old Way

The typical healthcare report is a static document delivered in a one-size-fits-all model. Revisions and updates are slow and time-consuming, often out-of-date at the time of printing.

The complexity of data available demands much more dynamic output.

Dynamic Displays

Look at the NYSE

Although nowhere as demanding, the rapidly moving and changing screens that we see on the floor of the NYSE and other financial centres, gives us an idea of how data can be displayed for the benefit of users.

Interactive, multi-coloured dashboards are available, showing data in easily-grasped formats. The data is updated in real-time or at least in short, frequent intervals.

Users can view critical metrics, trends, benchmarks and such.

Bells and Whistles

Complex data, when presented as easily-understood charts and tables, allow users to make confident decisions.


The Brave New World of Healthcare Data Analytics

Everywhere we turn, we keep seeing, reading or hearing about the rapidly expanding role of big data analysis and artificial intelligence. Computer power and software complexity have reached a point where hitherto fortressed domains are being breached. Recent reports of programmes generating sophisticated pieces of journalism that are hard to distinguish from human writing have induced a sense of fear in all professions. Robotisation revolutionised manufacturing. The automation wave is advancing relentlessly into white collared jobs and the service sector.

Healthcare has stayed defiantly refractory to the changes happening around it. This state can’t last for long. Major disruptions are in sight. Healthcare data analytics hold the promise for being a dominant force in bringing about a much-needed change in the area of healthcare delivery.


Catastrophic health expenditure

In simple terms, a catastrophic health expenditure is a healthcare-related bill that exceeds your capacity to pay. It often involves the encashment of savings and assets, including, at times, homes and businesses. It can impoverish and devastate families for many years.

Medicine is magical…(Paul Simon): Modern medicine is a great example of Arthur Clarke’s statement: “Any sufficiently advanced technology is indistinguishable from magic.” This magic show comes at a price. Formerly fatal illnesses can be salvaged by the ability to sustain and prolong life functions with machines, often well past the likelihood of meaningful quality of life after discharge.

Here’s the bill: In India, treatment in a fully-equipped Intensive Care Unit (ICU) with all life-support measures can cost a lakh or two rupees per day. Most ICU stays will last for a week to 10 days, some even more. So, do the math. In developed economies, the figures are equally high with proportional adjustments for living standards.

OOPs (out-of-pocket) expenditure: India has the world’s highest out-of-pocket (OOP) expenditure on health care – a stupendous 60% as opposed to the global average of about 15%. Here’s a graphic comparison.

Catastrophic health expenditure hits us Indians harder than any other society. It is estimated that catastrophic health expenditure impoverishes 3.3% of Indians every year.

  • It’s one of the leading causes of families being driven below the poverty line.

The need of the moment: More than any other, this devastating economic event makes a strong case for Universal Health Coverage (UHC) programmes. In advanced societies, particularly the United Kingdom and Western Europe, the existence of cradle-to-grave social welfare programmes buffers individuals from the cost.

The price of exit: It’s also worth pointing out that catastrophic health expenditure will usually occur in the last year or two of a person’s lifetime, contributing in no small way to the dissatisfaction with the spending. All this, only to see them die…?

Reference: Prevalence of catastrophic health expenditure and its associated factors, due to out-of-pocket health care expenses among households with and without chronic illness in Bangalore, India: a longitudinal study


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In memoriam: Side Kick and the days of yore

Some time ago, I read about and started using a wiki with an intriguing name: “TiddlyWiki”. It’s a wiki and less; a wiki that went on a diet, shed large amounts of flab and emerged leaner and meaner. It’s a single html file that requires nothing special, no server, no geekspeak, works through your browser and does everything a wiki should. Jeremy Ruston (may his tribe increase), its creator, describes his brainchild as a non-linear, personal notebook. It has the austere simplicity of a Google opening page and, likewise, packs a punch. It grows on you and continues to amaze with its elegance. Explore it at TiddlyWiki.com.

This essay is not about TiddlyWiki but something that set me thinking in its wake. My first personal computer was bought after a lot of quick talking to my wife about how it would save my soul: an Apple II plus. The year was 1980. The box was all you got for a thousand plus dollars. I bought a small car the year before for about four thousand, so that should put things in perspective. No monitor; you hooked up to your TV set. No disk drive; if you wanted a 180 KB floppy drive, that would add another fifty per cent to the cost. Forget printers; a thermal-paper-based one would chalk up another 300 dollars. The software came on music cassettes that you played on your cassette player and plugged into the computer. A whopping 48 KB (K, not M, not G) of memory. I loved it.

This memoir is not about Apple II pluses either. Then came my first “PC” — loaded with 256 KB (yes, K, not M) of memory and a floppy drive that used 360 K floppies (yes, K again, not M). The machine roared along if you bought the double drive version. This way, you didn’t have to take out the floppy with the programme software and put in a data disk every time you needed to save files. The two-drive system allowed the programme and the data to cohabit the same box. If you were wealthy, you could ask for a 10 MB (yes M, not G) hard disk that had the heft of a Tom Clancy novel and crashed at least once a week. Reformatting hard disks and reinstalling operating systems and software was all in a day’s work.

This memoir is not about the travails of working in a frontier land where men were men and so on. No doubt, like the cowboys of yore who carried everything they owned and needed in their saddlebags, not their pick-up trucks and SUVs, we travelled light. 

This brings me to what this memoir is all about; software that made you gasp, made you feel like the guy on a horse seeing Marlboro country for the first time. Appropriate to the current metaphor, it was called “Side Kick”. I believe that there was a space between the words; this was in the prehistoric days before wiki words and camel case. Somehow, after installing and working with hundreds of packages, I cannot recall any that gave me the high that Side Kick did. Remember, we were in an age where windows were washed regularly, not minimized. To run a second programme, you had to shut down the one you were with and fire up the one to follow. Multitasking meant talking with the phone cradled between your head and shoulder, trying not to get choked by the cord while frying eggs. In this background, Side Kick was a stunner. The entire package was about 50 K in size (K, not M). It was memory-resident, which meant that it could perform the miracle of staying in the background while another programme was running; a “Ctrl-esc” combo would wake it up. It popped up on top of your open programme in a resizable window and did not take up the entire screen. It could do several things at once: a calendar, a word processor, and a small database, amongst other things. You could save files from it. You could copy, cut and paste — all for 50K.

Okay, “So what?” the generation X-ers are saying as they slaughter a horde of slime-eating mutants on their Play Station. Like stout Cortez on the peak of Galen, you just had to be there to get the feeling. It’s like standing in line for hours to see the first Star Wars episode in the seventies. All film-making technology that has followed does not do the same for me that my first exposure to R2D2 and the Force did. I can’t describe it, but those of you who were there would know what I am talking about. 

Well, Side Kick died, and I don’t think anyone even cared. I would mourn, now and then and like in life, the now and then became further and further apart.  And then, TiddlyWiki! In the words of my contemporary, Barry Manilow, it was time to get the feeling again. TW weighs in at about 200K, minuscule in today’s world of software bloat that considers 50 MB as slim and svelte. TW is Side Kick born again, as Zen-like in its stark simplicity and majesty, which is the real reason for this memoir.

PS: If you mourn Side Kick, you will also remember PFS:File, in my opinion, the best flat-file database manager ever. Using the current version of Access is like trying to roll a fallen elephant with a toothpick.

The final exit: Dealing with terminal illness

No, it’s not just in the movies; it’s real. The person facing you has been deemed to have a poor chance of surviving for any meaningful period of time. A typical example would be one where an advanced stage of cancer has been diagnosed. It’s likely that the person has only a few weeks or months left in their lives based on data and statistics of good quality.

Going beyond: I am going to venture beyond the limits of this question. There are many major elements of terminal illness that are important. In my practice, this situation is possibly the hardest encounter I have had with patients and their families.

Be truthful, be gentle: The most important thing to do in this situation is to be truthful without being blunt; a lot of gentleness and empathy are needed.

  • Never deny hope, never give hard numbers and data; I prefer to speak in general terms.
  • Hiding information from a patient out of a mistaken intention of being kind actually does them a disservice. There are personal agendas and activities that may need to be fulfilled. The person should be given a chance to go after them.

Pain: An important question that always arises is the prospect of pain in the final days. There are strategies available that can keep them comfortable while maintaining clarity of mind. This has to be handled with confidence.

Home, not alone: I also advocate that the last few days be spent at home, in familiar surroundings, rather than in a hospital, cut off from family and close friends.

DNR: A “do not resuscitate” decision, once taken by the patient, has to be announced to the care givers. The issues at hand have to be clearly discussed ahead of time.

“Lies, damn lies, and statistics”: There is one important reason why I stay away from giving hard numbers. There is always a patient or two who goes well beyond the expected time frames and survives for much longer periods than predicted. The human body-mind is a mystery we cannot fathom.

Must read this: In conclusion, I would recommend reading a superb article on terminal illness written by the well-known evolutionary biologist, the late Stephen Jay Gould — objective and hopeful. The median isn’t the message


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Why is clinical reasoning important?

Reasoning is important in any walk of life, not just medical practice. It’s what sets humans apart from the rest of creation. Simply put, you encounter a situation, get some input or information from it, make a reasoned-out assessment, do some research on the subject, and then carry out a response.

The practise of Medicine involves the same approach but modified for the specific purpose of managing illness. The steps are:

  • History and physical examination.
  • Making a provisional diagnosis.
  • Ordering carefully chosen tests and investigations to clarify states of uncertainty.
    • Making a final diagnosis.
  • Outlining a management plan.

This process, done well, provides efficiency and economy; quality healthcare that is cost-effective. Even today, there are no short cuts or quick fixes.

A detailed history and a careful physical exam will, in most cases, be all that is needed to make a confident diagnosis. This is often skipped or done in a very cursory fashion. It’s quite common to hear patients complain that the doctor didn’t listen to what the patient had to say, didn’t lay hands or examine at all, and proceeded to write out a string of investigations and medications.

Unfortunately, largely due to the plethora of tests and investigations that are on offer, the chain of reasoning is dispensed with. There is a misplaced belief that tests will tell us what’s going on. Panels of tests are ordered, most of which are unnecessary. A shotgun approach is taken, frequently under the guise of time constraints.

Unthinking testing will often complicate, rather than clarify, states of uncertainty. False positive results will set off another round of probing in the chase of a chimera. False negative results will provide false reassurance.

Overdiagnosis and medicalisation are problems that come out of unthinking approaches to patient care.

Structured, algorithmic, evidence-based clinical reasoning has always been and always will be the backbone of good medical practice.


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Electronic health records

Without the need for words, this graphic encapsulates the problem with physical, paper-based health records.

Electronic health records (EHR) are very much a basic requirement for modern healthcare delivery. The advantages are numerous.

  1. Multiple user access: The physical record can be viewed only by one user at a time. The EHR canbe seen by any number of authorised users.
  2. Multi-site access: Like all electronic information, the EHR can be viewed anywhere—across cities, states, countries, …
  3. Indestructible nature: With adequate backups (and that’s a given today), the EHR is everlasting. Physical records deteriorate over time, even in the most controlled of environments.
  4. Space saving: The Medical Records Department of earlier times occupied vast spaces, yet always needed more. EHRs: You know the answer.
  5. Graphical interface: With well-designed user interfaces, data capture can be made more efficient. Any number of devices and methods are available to make the task easy.
    1. Custom views can be tailored to meet the demands of specific practise styles.
  6. Decision support systems (DSS): Decision support systems can be built into EHRs. If you need to look at a lot of different types of data in a complicated medical situation, a DSS can be very useful.
  7. Data analysis and reporting: No modern hospital can function without continuous monitoring of a number of clinical outcomes. Handwritten records are much harder to analyse than EHRs.
  8. Knowledge building: Data mining, machine learning, and artificial intelligence can all be used to build knowledge bases that are highly relevant to a given practice environment.
  9. Coding and billing: Sophisticated coding systems like SNOMED-CT can be smoothly integrated with EHRs.

BUT, doctors don’t like electronic health records!

Doctors, including many who see themselves as tech-savvy, resent using EHRs. They feel that it interposes an unwarranted presence between them and their patients. Almost uniformly, doctors have to spend more time working with digital records than paper. They feel that EHRs have worsened, rather than improved, clinical care delivery.


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