Algorithms in #EMR by Dr. Joyoti Goswami




Practicing physicians these days are barraged with a lot of technical jargon promoted by the Information technology professionals such as Big Data, Hadoop, Artificial Intelligence and Predictive analytics. For a physician not introduced to the these terms, the conversation is of little value unless there is a specified value in the clinical setting.

Pulitzer Prize winning author Siddhartha Mukherjee in his book ‘Emperor of Maladies’ has quoted “The greatest clinicians who I know seem to have a sixth sense for biases. They understand, almost instinctively, when prior bits of scattered knowledge apply to their patients—but, more important, when they don’t apply to their patients.”

So the accumulation of all the 6th sense of multiple physicians in the form of scattered notes in documents is the food for Big Data professionals, who curate this data manually with standard vocabularies and then analyse patterns that can help physicians make informed decisions at the point of care.

While Predictive Analytics is a huge winner if there is genomic data available, the fact remains that in current clinical scenarios, complete genomic sequencing is not yet the norm. They are still restricted to the areas of research as the cost of doing a complete sequencing of the genome is still about $ 1000 and very few institutions are prescribing it as a norm in routine clinical practice. Once that is in place, it can lead to a whole lot of practical applications and use cases making the use of technology like Big Data and Hadoop. 

Till then, use cases which use traditional computing powers like SQL and simple queries and algorithms running on top of it could be used to get the benefits of clean data and technology in the clinical workplace.

In an attempt to utilize Predictive Analytics and Artificial Intelligence in the world of EMR and healthcare data, a list of 5 practical clinical use cases and 5 administrative/Claims Related use cases of how data could be used at the point of care and integrated with the EMR is listed out below:

Clinical Usecases

1 Acute Kidney Injury

According to Statistics, 1.2 million people per year get AKI during a hospital stay and 300,000 people in the US die annually due to AKI, this is more than breast cancer, prostate cancer, heart failure and diabetes combined. 

The successful documentation and implementation of the AKI algorithm published by the NHS is a systematic and step by step program that can help reduce the incidence of Acute Kidney Injury and the mortality and comorbidities associated with it. The e-alert for AKI installed in the LIMS (Laboratory Information Management Systems) alerts physicians when a patients’ Serum Creatinine rises greater than 26 mmol/litre from a baseline within 48 hours or there is a rise of 50% or more in 7days and/or the urine output is < 0.5 ml/kg body weight/hour. https://www.england.nhs.uk/wp-content/uploads/2014/06/psa-aki-alg.pdf

2 Sepsis Management

Sepsis or SIRS (Systemic Inflammatory Response Syndrome) accounts for 20 to 30% hospital deaths and $15.4 billion in annual healthcare costs. Needless to say early diagnosis and treatment is critical to optimal care. 

In a study, it was found that 24% of infected patients with 2 or 3 qSOFA (or Quick Sepsis Related Organ Dysfunction Assessment) points accounted for 70% of the deaths. An automated EMR based Sepsis identification system helps to detect cases with sepsis. A sepsis sniffer algorithm in ED identifies patients who exhibit at least 2 of the 3 criteria of Altered Mental Status, Fast Respiratory Rate and Low Blood Pressure and initiates the Sepsis Order set if the results of the score warrant it. The content on the Sepsis Order Set helps to make sure that none of the key variables for the management of sepsis is missed out.
https://www.mdanderson.org/documents/for-physicians/algorithms/clinical-management/clin-management-sepsis-management-adult-web-algorithm.pdf

3 Initiation of Statins

Mayo clinic has implemented a single click decision support tool within the EMR to automate the calculation of 10-year atherosclerotic   cardiovascular risk and populate the statin choice decision.  Based on the risk score calculation parameters of the ASCVD (atherosclerotic cardiovascular disease), the tool populates whether the patient needs a statin or not and if yes, which statin would be the best choice. This is defined on the basis of an algorithm running which has historical data of similar patients along with their outcomes.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157431/

4 Algorithm to identify major cardiac adverse events while on statins

Cardiovascular disease is a leading cause of death worldwide and statins are largely prescribed for the same. A study was conducted using historical data to identify patients with MACE (Major Adverse Cardiac Events) while on statins for primary prevention.  This algorithm achieved a 90 to 97% positive predictive value for the identification of adverse cardiac events while on statins
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333709/

5 Detection of Diabetic Retinopathy

Diabetic retinopathy is the fastest growing cause of blindness and screening patients with diabetes for retinopathy has been mandated as part of all the Quality Measures such as MIPS, HEDIS and others. Google analysed a dataset of  128,000 images of the retinal fundus and used that to predict retinopathy based on the lesions present on the scan such as microaneurysms, haemorrhages, exudates etc. A blindfold comparison of the results predicted by the AI algorithm was compared with the results given by experienced ophthalmologists. The AI algorithm had an accuracy of 90% which is a huge win especially in areas where there is a shortfall of specialists to interpret the results.

In the areas of diagnostics especially interpretation of Imaging results, a lot of good work is going on and soon AI capabilities will lead decision making in the interpretation of reports.
https://ai.googleblog.com/2016/11/deep-learning-for-detection-of-diabetic.html

Physicians working closely with Data scientists can help create some exciting algorithms given that healthcare centres today have large volumes of data sitting in their EMRs. A physician with even 50 patient records of 2 years has sufficient information to derive useful insights on predicting interesting patterns on the future health and preventive measures therefore can be planned accordingly. The approach for healthcare institutions should be to first identify their most pressing problems and then evaluate if any kind of Prediction of solutions to those problems could lead to better outcomes in patient care. A well thought and organized approach could go a long way to develop algorithms that work well for the hospitals and ambulatory clinics to achieve their goals and have favourable outcomes for both the patient and the hospital.

Administrative Use Cases:

In Patient Registration systems and billing systems, the algorithms can have a different flavour, some of which are listed below:

1. Healthcare Utilization Management: Integration of hospital resource utilizations in different departments, risk management and quality assurance into a management dashboard in order to ensure the judicious use of the facility's resources. A review of the procedures and services rendered by the hospital and the resources used by them (such as rooms, timings, instruments, admin and clinical staff) can help to identify under utilized and spare capacity of the hospital. This can be inbuilt in the system with the help of algorithms so as to get an optimal effect.

2. Capturing Missed and Incorrect Charges: Many facilities lose revenue due to billing errors done manually. Billing amounts associated with each DRG (Diagnosis Related Group) can be used to create models and compare them with the actual billing. Outliers in patient invoices can help to identify the likelihood of missing or incorrect charges. The higher prioritized invoices can then be reviewed to confirm the charges, which may be incorrect, over billed or under billed.

3. Predicting denials: There is a constant tug of war between the providers and payers about the claims to be settled. Most of the denials are due to incorrect documentation or missing information, duplicate claims, service already paid as a part of bundled services or others, services not covered by payer and late submission of claims. All of the above can easily be avoided by streamlining coding and billing processes. The industry benchmark for medical billing denials is 2% and in practices between 5% to 10%. Reworking on denials has a cost associated, so having algorithms running within the systems can help to streamline these efforts.

4. Predicting wait times and No shows: Idle time in clinics, both for patients and providers can be frustrating. In departments where procedures are done, it is possible to predict treatment durations by looking at historical data. Similarly the number of no shows of scheduled appointments can be predicted by including variables like age of patient, severity of disease, previous appointment regularity of the patient and others. This could help the facility to take in additional patients on the free slots proactively.

5. Measuring Bad debt, Days in A/R and DNFB (Days in Total Discharged Not Final Billed): These metrics help to determine the effectiveness of the claims generation process and effectiveness of collection efforts.

A number of KPIs tracked by hospitals and payer systems can be in built within the Revenue Management Systems and Scheduling systems. These include patient costs, ROI of the facility, Average Patient Wait times, Average patient appointment scheduling times and Patient Satisfaction.

With the healthcare market growing and many EMRs, both locally created and branded companies in the play, it is eventually the content within the EMR that can make it user friendly. Many content companies offer excellent standardised algorithms and content that can be integrated within the EMR, but there always remains physician preferences based on specialty, region of practice and other personal preferences. The end user i.e. the physician ultimately needs to decide on what suits his practice and then have the algorithms accordingly tailored within the EMR.

Author
Dr. Joyoti Goswami
Healthcare expertise of over 20 + years. Clinician having worked in specialty hospitals as medical officer and currently in the Healthcare Information Technology domain since the last 10 + years. Have a good combination of clinical and technology skills in multiple areas. Worked with multiple EMRs such as Allscripts, GE Centricity, Athena health and Nextgen
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#RPA in Healthcare: The Path Ahead for Health IT Leaders By Sreejith Madhavan



Historically, healthcare industry has shown a reluctance to invest in technologies that did not come under the purview of diagnostics and treatment, or demanded by insurance payors (such as electronic claims submission). Anything that required cognitive (human) intervention or intuition was kept aside from the technological takeover. The unprecedented growth of life expectancy, the discovery of new drugs and treatments, and the ability of modern medicine to combat chronic ailments and epidemics have spurred the need for technological inclusion in multiple areas of healthcare.

As patients become more digital savvy, caregivers are increasingly implementing technology solutions that enable both parties to perform several activities online such as accessing personal medical information to online scheduling of appointments. Today, healthcare industry is looking at those technologies or combinations of technologies that can optimize their front, middle and back-office operations so that care givers get adequate time to spend on priority tasks.

Robotic Process Automation (RPA) is one of the key technologies that has gone mainstream in many industries including healthcare. Why health IT leaders should continue to turn their pivot towards RPA? We’re exploring the reasons through this post.

RPA in Healthcare: Common Applications and Benefits

Robotic Process Automation or RPA automates processes that are repetitive and transactional, primarily by imitating human behavior for rule-based tasks.  RPA enables caregivers to focus on high-value activities by enhancing overall administration of healthcare processesIt executes routine tasks at a fraction of time than that’s taken by a human, eliminating the risk of human errors. The scope of RPA in the administrative and clinical functions of healthcare is very vast. 

Technologies such as cloud computing and data virtualization have enabled scalable deployment of RPA software across various units and geographic locations of a healthcare organization. So far, healthcare administrators have leveraged RPA in several areas of their back, middle and front-office operations; few of which are mentioned in the table below:  


Healthcare

Areas of RPA implementation
Benefits to healthcare providers
Back Office


  • Human resource management
  • Finance and supply chain management
  • Streamline onboarding process to improve efficiency
  • Clinicians can impart care without interruption caused by administrative functions
  • Human resource management
  • Ensure new clinical staff gains access to systems and facilities from day 1
Middle Office


  • Revenue cycle management
  • Claim submission and reconciliation
  • Patient scheduling
  • Accelerate revenue cycle by automating coverage eligibility verification process, claims posting, and claim resubmission
  • Insurance data management
Front Office

(relatively untapped by RPA)


  • Care delivery setting
  • Health data utilization and report generation
  • Integration of disparate care management systems to assimilate date efficiently
  • Ensure clinicians spend more time for patient care by minimizing their administrative work
  • Enhance case management

Most of the present day healthcare organizations are using RPA for automating rules-driven and repetitive back office work. The potential RPA can offer healthcare in unison with advanced technologies such as machine learning (ML) and artificial intelligence (AI) is tremendous. It’s no surprise if we consider Robotic Process Automation a stepping stone to integrating these sophisticated cognitive technologies into healthcare.

What needs to be automated in healthcare?

Here’re a few potential use cases: 

1 Connecting and automating disparate health monitoring devices: The case of neonatal ICU:

A 2017 Business Insider post talks about the need to automate oxygen supply to patients hospitalized with pulmonary hypertension. Currently, the system only alerts the staff (nurse) through a monitor beep when the blood oxygen level of the patient drops and the staff has to attend the case. If the nurse is attending other patients and misses out the alert, the chance for a mishap is more. The article from Thomas Hooven, a Neonatologist in the U.S. suggests how automation of oxygen inflow at the moment of crisis could save patients with chronic pulmonary hypertension.

2 Compliance monitoring and analysis:

Imagine a hospital that processes thousands of claims daily and attends the need of a large number of insurance beneficiaries. RPA can be used to gather and consolidate data from multiple disparate sources or systems that improves the efficiency of regulatory, non-financial, and risk reporting. Automation of compliance monitoring analytics eliminates time-consuming activities involved in the collection, compilation, cleansing and summarization of large amounts of information. Security of medical data and records is a major concern for any healthcare organization. Robotic Process Automation helps protect patient privacy and achieve compliance with HIPAA and other mandatory health regulations by generating custom reports and detailed audit logs.

3 IoT analytics to empower process automation

The goal of any IoT deployment should not be limited to collecting data from multiple sources (devices). It must ensure that the data is actionable in real-time, to support relevant processes. Process automation is recognized as the common endeavor to improve operational efficiency by lowering costs, increasing profits and improving customer satisfaction. Integrating IoT into process automation could deliver greater value across product lines. For instance, consider the claims settlement process in healthcare that is deeply influenced by the data being collected from several devices. During the claims settlement process, if the system could take into account the details of the data aggregated by IoT devices such as lowering a premium based on usage behavior, or a difference in user-provided information, that could lead to process optimization and faster decision-making. IoT analytics in healthcare can avoid the cost of admissions by automating prescriptions, reduce medical error in treatment and improve quality of patient services.

Leveraging RPA with exponential technologies

RPA is just one of the growing technologies that can empower healthcare organizations. Once RPA is integrated successfully into their core business strategies, hospitals should consider incorporating the advanced spectrum of cognitive technologies such as AI and machine learning. Unlike RPA, artificial intelligence has the ability to identify patterns in data. Similarly, machine learning adds more meaning and power to process automation by enabling healthcare organizations to identify payment variance and remediate complex payment methodologies.

The future healthcare environment could look very different from what we see today. Technologies like Robotic Process Automation will have a greater say on employee productivity. Automating routine tasks such as collecting blood samples could help the job of a nurse, reduce task time and eliminate manual errors, while improving the patient experience. As organizations progress from depending on manual tasks to applying RPA and cognitive computing, the workforce also shifts from being “doers” to “reviewers.” Health IT leaders and providers, hence should focus on developing proactive, winning strategies to attain long-term financial sustainability and improved patient experience.

Author
Sreejith Madhavan
Sreejith Madhavan is the Chief Operating Officer of Zerone Consulting Pvt. Ltd., a custom software development company with an exceptional track record of successfully completing over 500 challenging projects for 140 plus satisfied customers globally. Sreejith’s experience includes a demonstrated history of working in the outsourcing/offshoring industry, managing and mentoring multiple teams in the web and mobile development arena
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What does it take to build real-world #AI enabled healthcare solution? By Vijayananda J, @vijayanandaj



Development of new technologies has undoubtedly enabled several breakthroughs in the healthcare industry. To put it simply, it has revolutionised the growth of healthcare from nascent patient-care to accomplishing treatment of life-threatening diseases. High-performance computing and the availability of digital data have extended these remarkable outcomes explaining why AI-based healthcare solutions are at top of the funding lists and are continuously gaining traction.

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NITI Aayog’s National Health Stack - a Healthy Stack?! by Divya Raj @divyaraj1




Extraordinary problems need extraordinary solutions. And creating a country level IT infrastructure addressing challenges in India's Healthcare management for its 1.3 billion population definitely falls very well into that category. 

NITI Aayog's “National Health Stack - Strategy and Approach” document published in July ’18 is a good starting point in the direction of digitizing India's healthcare management for meeting the challenge of healthcare of India's masses. It’s a clear reflection of the realization that India’s Healthcare needs a digital infrastructure. The National Health Stack (NHS) is outlined as a "visionary digital framework" with four key components -- electronic health registries of health service providers and beneficiaries, a coverage and claims platform, a federated personal health records framework and a national health analytics platform. 


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#Blockchain in Healthcare: Will it or won't it survive? By Tirupathi Karthik, @TirupathiKarthi




What is Blockchain

Blockchain offers a permanent record of online transactions. Transactions are deemed as a “Block” and a ledger binds them in a “chain” thus earning its moniker “Blockchain”. Each transaction is validated and stored by a network participant based on rules but sans a governing central authority. Information can neither be modified nor copied or deleted.

Every transaction has a time and date stamp, offering a trusted transaction history and allowing verification of such records. Since the information is encrypted, the only way to access the blockchain is with a passcode. This shared ledger system makes Blockchain rather secure. Given this, Blockchain is gaining new use cases for applications that require trusted and immutable data.

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Containing Health Care Cost, What is our role as a Physician? by Dr. Chandrika Kambam @Ckambam




Indian health care is at an inflection point. Today governments’ spending on healthcare needs is one of the lowest amongst the Developing countries [1]. India spends about 5% of the total expenditure on Health which is around 1.7% of the GDP. Public healthcare growth has slowed down over years. In 1998 about 43% of population was served by Public Hospitals and today only 30% use the Public health care system. [2] That means almost 70% of the health care needs are serviced by Private players, trust hospitals and non-profit institutions. This has led to the rapid growth of Private players who are growing at the rate of CAGR 16.5% year on year [3]. The costs of procedures or hospitalization has increased anywhere from 83% to 263% in 10 yrs. i.e. 2004 to 2014. There is also a wide variation of the cost for the same procedure in different hospitals [4]. It is also noted that 86% of rural Indian patients and 82% of urban Indian patients do not have access to any form of employer-provided or state-funded insurance.

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Software Product For Hospital Industry by Girish Koppar @KopparGirish



Before we talk about software product for hospital industry lets understand how the Hospitals are broadly classified

- Based on the legal entity ( Private , Trust or Corporate)
- Based on specialty ( Super specialty, Multi-specialty, Single specialty)
- Based on bed strength ( Larger hospitals and Nursing Homes)

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Electronic Health Record System from the Perspective of Data Privacy by Dr. SB Bhattacharyya @sbbhattacharyya

Electronic health record systems handle health-related ultra-sensitive data of a person throughout his life, along with all personal information that accurately identifies him. This makes it imperative to protect the data from cyber-threats and consequent untold damages. This article discusses the various issues involved and the different mitigation methods.

During the course of any clinical encounter a person discloses ultra-sensitive health related information to his provider to enable the latter to address his health-related problems better, faster, and hopefully, cheaper. Information that he would otherwise rather keep well under wraps. Ethics demands all providers treat all information that their patients disclose to them with the greatest of care and keep them secreted away from everyone, even the spouse, unless explicitly released from this obligation by the patient. The confidentiality of the private information needs to be maintained at the highest possible levels of security by medical professionals at all times—unless there are extenuating circumstances to disclose them, like for the public good, compliance to the law, etc.

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A Data Scientist’s Experience in Decoding Chest Imaging by Vidya MS



The Chest Imaging Update 2018 held by the Narayana Health group, brought together over 150 radiologists, pulmonologists and doctors gathered to update and improve their knowledge in the reporting of Chest Imaging, both X-ray and CT. As a data scientist with keen interest in medical imaging, my aim was to get an inside look into the daily practice of medical professionals in detection and diagnosis of pulmonary diseases.
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PregBuddy’s year with Google Launchpad by Sivareena S. L. @SarikaSivareena




We’re all aware about the Google Launchpad accelerator which selects pre-series A startups across the globe every year to assist them scale their business. Along with this, Google Launchpad has few more offerings where they have extremely well structured programs for various stages of startups. Pregbuddy has benefited from couple of these programs as we grew our product.

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Almighty Data or Hype? By INDERJITH DAVALUR @INDERDAVALUR

DIGITAL TRANSFORMATION AND THE PLACE FOR DATA

Mea Culpa, I am one of those who is guilty of getting on and staying on the Big Data wagon for the wrong reasons. “Data is the new oil” is an oft-repeated phrase. I am about to commit a “virtual” suicide by proclaiming that it is not so. Data has its place and it is not at the top of the digital food chain. I feel that we have crowned the half-naked prince, Emperor in haste.

For the sake of clarity, when I say data, I will be referring to digital data throughout this piece. Data is a by-product of any activity. Therefore, creating data is as natural as breathing. So we have data. A lot of data. So what? Accumulating data, structuring it, storing it, analyzing it are a natural progression from that point onwards. How and what we do with the data is more important. Software. 

The magic that is software, to me, is more transfixing. Consider the prospect of a language written in a semantic that is alien to our natural human language. A cryptic command, logic, condition, trigger – anything at all – that is magically read, understood and acted upon by silicon. Hardware that contains baked-in code that can parse and carry out complex instructions at blazing speeds. Pieces of such chips soldered on a board and communicating through ‘roadways’ of circuits laid out on a board. The miracle of hardware coupled with the magic that is software is what gets my adrenalin pumping. How can such a marvel not be exciting?

Even the awesomeness of hardware pales in comparison to software. Hardware is more or less static. It is confined to physical and functional dimensions. Software, however, is supreme. It can use the same hardware (with some limitations of course) and carry out simple tasks, entertain with games, or perform wildly complex calculations at very very high rates of speed, accurately all the time. And it can do this million million times with alacrity. This is just the beginning of what software can do. But wait, there’s more!

Consider intelligence in software. It suddenly becomes a living, breathing, dynamic being. Almost. Software can learn and teach itself. Crunching data and spitting out patterns and actionable analysis suddenly becomes mundane, banal almost pedestrian. No. I am not against data or big data. By itself, big data is just that. A monstrosity. Sometimes, big data actually gets in the way. Misleads us in making decisions quickly. Software breathes life into data. 

Take any software language or tool. Examine it. Study its flow, the eloquence, the nuance and its brilliance. Brevity in software coding is revered by programming perfectionists. There is elegance in a well-written piece of code that executes beautifully, perfectly, every time. Anyone that can find literary melody in Shakespeare or Milton can certainly begin to enjoy the harmony in a beautifully crafted software application code. So, my appeal goes out to all those who are worshipping big data to take a moment to reflect upon the joy that software brings to our daily lives. After all, the future is software!

Author
Inder Davalur
Inderjith Davalur is a healthcare technology specialist, speaker, writer and utopian dreamer.
Inder works with hospitals committed to transforming the healthcare paradigm with the aid of new innovative technologies. His primary area of interest lies in using data analytics and technologies such as Deep Learning to shift the current physician-driven healthcare model to a patient-driven market dynamic.
Inder focuses on the manifold ways in which data crunching and machine learning can lead to better diagnoses that can not only be made at the time of illness, but predicted way before any symptoms surface. The path ahead in the sector, he believes, lies in the deployment of evolving technologies that immensely influence both diagnostic and therapeutic aspects of healthcare, delivering real patient-driven, data-enabled, informed healthcare.
Inder currently works as the Group CIO at KIMS Hospitals Private Limited, Hyderabad and has previously assumed leadership roles at leading hospitals and companies, in India and the United States of America.
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Simplifying Health Economics by Dr. Karan Sharma

After hearing about India's New Health Insurance Program, I thought it is good idea to share about Health Economics, so here I am

Health economics is a branch of economics concerned with issues related to efficiency, effectiveness, value and behavior in the production and consumption of health and healthcare. 
Alan William Plumbing Diagram about Health Economics
I am using Alan Williams “Plumbing Diagram” to comprehensively understand Healthcare Economics. He has divided scope of healthcare economics into eight distinct topics (explained in the documents) which are:
·        What is health and what is its value?
·        What influences health? (other than healthcare)
·        The demand for healthcare
·        The supply of healthcare
·        Micro-economic evaluation at treatment level
·        Market equilibrium
·        Evaluation at whole system level
·        Planning, budgeting and monitoring mechanisms.
There are interlinkages between each topic, which make it possible to see Health Economics as an integrated whole – more than an Ad-hoc assemblage of topics. According to understanding – The first five boxes
(A) Health and its values,
(B) Influencers to health,
(C) Demand for healthcare,
(D) Supply of healthcare and
(E) Market equilibrium factors are the analytical “Engine” of health economics.

The remaining three (F) Microeconomic evaluations, (G) Planning, budgeting and monitoring and (H) Evaluation of system are main area of Applied Economics. 
Let us understand each topic and its relationships:
CORE ENGINE
A.    Health 
Health can be defined as physical, mental, and social wellbeing, and as a resource for living a full life. It refers not only to the absence of disease, but the ability to recover and bounce back from illness and other problems.
Health generally evaluated through its value and perceived attributes, which are like:
1.     Productivity of individual healthy days
2.     Value of life
3.     Expenses caused by diseases and etc.
Health can be treated both as consumption and an investment good, Consumption: health makes people feel better, Investment: it increases the number of healthy days to work and to earn income.
Health does have characteristics that more conventional goods have; it can be manufactured; it is wanted and people are willing to pay for improvements in it; and it is scarce relative to people’s wants for it. It is less tangible than most other goods, cannot be traded and cannot be passed from one person to another, although obviously some diseases can.
B.     Influencers
According to WHO, many factors combine together to affect the health of individuals and communities. The few factors which affect health include:
1.     Income and social status - higher income and social status are linked to better health. The greater the gap between the richest and poorest people, the greater the differences in health.
2.     Education – low education levels are linked with poor health, more stress and lower self-confidence.
3.     Physical environment – safe water and clean air, healthy workplaces, safe houses, communities and roads all contribute to good health. Employment and working conditions – people in employment are healthier, particularly those who have more control over their working conditions
4.   Social support networks – greater support from families, friends and communities is linked to better health. Culture - customs and traditions, and the beliefs of the family and community all affect health.
5.     Genetics - inheritance plays a part in determining lifespan, healthiness and the likelihood of developing certain illnesses. Personal behavior and coping skills – balanced eating, keeping active, smoking, drinking, and how we deal with life’s stresses and challenges all affect health.
6.     Health services - access and use of services that prevent and treat disease influences health
7.     Gender - men and women suffer from different types of diseases at different ages.
There are evidences available of other examples which has been documented which are like: Transport, Food and Agriculture, Housing, Waste, Energy, Industry, Urbanization, Water, Radiation, Nutrition etc.
C.     Demand
Health demand is to achieve larger stock of Health Capital (healthy days). It is not passively purchased from market; it is produce in combining time with purchased medical inputs. Both value of Health and its influencers affect the demand. 
The demand for health is unlike most other goods because individuals allocate resources in order to both consume and produce health. There are four roles of person in health economics:
1.    Contributors
2.    Citizens
3.    Provider
4.    Consumers
 In the context of ordinary goods and services, economics distinguishes between a want, which is the desire to consume something, and effective demand, which is a want backed up by the willingness and ability to pay for it. It is effective demand that is the determinant of resource allocation in a market, rather than wants. But in the context of health care, the issue is more complicated than this, because many people believe that what matters in health care is neither wants nor demands, but needs. Health economists generally interpret a health care need as the capacity to benefit from it, thereby relating needs for health care to a need for health improvements. 
Not all wants are needs and vice versa. For example, a person may want nutrition supplements, even though these will not produce any health improvements for them; or they may not want a visit to the dentist even if it would improve their oral health.
Healthcare has its peculiarity that may mean, it is not considered as any good or service where demand can be analyzed, however that the usual assumptions about the resource allocation effects of markets do not hold meaning for healthcare. Moreover, it may well be that people wish resource allocation to be based on the demand for health or the need for health care, neither of which can be provided in a conventional market. 
D.    Supply
Supply is to achieve and fulfill the demand of health. The supply side of the market is analyzed in economics in two separate but related ways. One is related to the Resource input and Goods output model, looking at how resource use, costs and outputs are related to each other within a system.
Important influencing factors to supply are as follows:
1.     Cost of production of service
2.     Alternatives of services
3.     Substitutes of inputs
4.     Remuneration and incentives
5.     Medical equipment and pharmaceutical markets
Other way in which supply is analyzed is Market structure – how many firms are there supplying to a market and how do they behave with respect to setting prices and output and making profits. These generally managed through market equilibrium
E.     Market equilibrium 
State where economic forces like demand and supply balanced. For healthcare many believes, it is imperfectly competitive market (Nash Equilibrium) where there is strategic interdependence between two firms. The Nash equilibrium occurs when both firms are producing the outputs which maximize their own profit given the output of the other firm. The other side believes it is competitive market. Market equilibrium factors are as follows:
1.     Money (payer), investment etc.
2.     Price mechanism
3.     Time price factors
4.     Waiting list
APPLIED ECONOMICS
F.      Micro-economics evaluation
In simple words it is decision making related to allocation of resources. Major goal of microeconomics is to analyze the market mechanisms that establish relative prices among goods and services and allocate limited resources among alternative uses. It also analyzes market failure, where markets fail to produce efficient results. Few topics which would play important role in micro economics evaluation are:
1.     Cost effectiveness and cost benefit analysis of alternative treatment
2.     Cost utility analysis
3.     Opportunity costing
4.     Allocation based on phases of disease (Detection, diagnosing, treatment and after care)
5.     Market structure
Healthcare market typically which are analyzed are:
1.     Healthcare financing market
2.     Physician and Nurse services market
3.     Institutional service market
4.     Input factors market
5.     Professional education market
G.    Planning, Budgeting and Monitoring
Optimizing the system through effective instruments and tools, few are as follow:
1.     Budgeting
2.     Manpower allocation
3.     Regulation and norms
4.     Incentives structure
H.    Evaluation of system
It is to bring efficiency and equity to the system to bear on (E) Market equilibrium and (F) Micro economic factors through inter regional comparison, international comparison and benchmarking.
Efficiency - the allocation of scarce resources that maximizes the achievement of aims by Knapp.
Equity is always an important criterion for allocation of resources. However, it is observable that people attach more importance to equity in health and health care than they do to many other goods and services. It is important to distinguish equity from equality. Equity means fairness; in the health care context this means a fair distribution of health and health care between people and fairness in the burden of financing health care. Equality means an equal distribution, but it may not always be fair to be equal. 
Health economics has number of methodological limitations but it can offer us useful concepts and principles which help us think more clearly about the implications of resource decisions. An understanding of some basic economic principles is essential for all practitioners not only to understand the useful concepts the discipline can offer but to appreciate its limitations and shortcomings.
Wish to hear more from my connections on this...
The article was first published on Dr. Karan Sharma's LinkedIn pulse page here, its been re-published here with the Author's permission. 
Author
Karan Sharma
Healthcare Strategy and Customer Experience Manager, Technology Enthusiast, Innovator and Healthcare Business Leader.

Highly experienced and focused senior Executive with strong background in Healthcare strategies and business problem solving. Have managed multiple projects in different disciplines and geographies with strong track record of building great teams with exceptional results. Provide and Execute vision, strategies or idea.

He is a clinician and healthcare management professional, worked in India, Middle East and Maldives.
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